Architectural enablers and concepts for mm-wave … enablers and concepts for mm-wave RAN...

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5G PPP mmMAGIC Architectural enablers and concepts for mm-wave RAN integration Date: 2017-03-29 Version: 1.0 Editor: Krystian Safjan - Nokia Bell-Labs Authors: Patrik Rugeland, Miurel Tercero Ericsson Yilin Li, Jian Luo Huawei Claudio Fiandrino, Joerg Widmer IMDEA Miltiadis Filippou, Honglei Miao Intel Krystian Safjan, Arnesh Vijay Nokia Bell-Labs Isabelle Siaud, Anne-Marie Ulmer-Moll Orange Rui Li, Mehrdad Shariat Samsung Javier Lorca, María Teresa Aparicio Telefónica I+D

Transcript of Architectural enablers and concepts for mm-wave … enablers and concepts for mm-wave RAN...

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5G PPP mmMAGIC

Architectural enablers and concepts for mm-wave

RAN integration

Date: 2017-03-29 Version: 1.0

Editor:

Krystian Safjan - Nokia Bell-Labs

Authors:

Patrik Rugeland, Miurel Tercero – Ericsson

Yilin Li, Jian Luo – Huawei

Claudio Fiandrino, Joerg Widmer – IMDEA

Miltiadis Filippou, Honglei Miao – Intel

Krystian Safjan, Arnesh Vijay – Nokia Bell-Labs

Isabelle Siaud, Anne-Marie Ulmer-Moll – Orange

Rui Li, Mehrdad Shariat – Samsung

Javier Lorca, María Teresa Aparicio – Telefónica I+D

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Executive Summary

The following white paper discusses key architectural aspects of the mm-wave RAT

(Radio Access Technology) working in frequency bands from 6 GHz to 100 GHz

integrated with new and other legacy technologies. Five architectural enablers were

identified. The first enabler is multi-connectivity that allows the integration of mm-

wave technology with low-band system and contributes for the improvement both in

terms of reliability and performance. Second key enabler is a new mobility state,

namely RRC_INACTIVE, which helps protect system from extensive signalling related

to infrequent small packet data transmissions. The third enabler is mm-wave cell

clustering, rendering a solution for dealing with propagation blockages and frequent

changes of the serving access point. Mm-wave cell clustering helps to perform cell

switching in a rapid fashion without introducing overwhelming amount of signalling

towards the core network. A fourth enabler is network slicing, which will allow

multiple logical networks to share a common physical infrastructure. The last enabler

is self-backhauling which, when coping with ultra-dense and cost-effective

deployments, is the best transport network solution in this scenario at the moment of

writing. Apart from these key enablers, we present new network functions that bring

significant benefits to mm-wave system operation. These functions are: power

efficiency oriented KPIs, upper layer optimizations for mobility; reference signal

design to support active mode mobility in beam-based Radio Access Network (RAN);

low frequency-assisted initial access beam training; user position prediction; user

localization; and environment mapping to improve mobility.

Table of Contents

1 Introduction ........................................................................................................................... 5

2 Generic Architecture ............................................................................................................ 6

3 Vertical Multi-RAT/RAN management .............................................................................. 7

4 Architectural enablers .......................................................................................................... 9

5 RAN functions and network integration........................................................................... 16

6 Conclusions .......................................................................................................................... 23

7 Acknowledgement ............................................................................................................... 24

8 References ............................................................................................................................ 24

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List of Acronyms and Abbreviations

4G Fourth generation

AoA Angle of Arrival

AP Access Point

AS Access Stratum

AWGN Additive White Gaussian

Noise

BRS Beam Reference Signal

CH Cluster Head

CN Core Network

CP Control Plane

CSI Channel State Information

DC Dual connectivity

DL Downlink

ECM EPC Connection Management

EIRP Emitted Isotropic Radiated

Power

eNB evolved Node-B

EPC Evolved Packet Core

E-

UTRAN

Evolved UTRAN

FEC Forward Error Correction

GLB Green Link Budget

gNB NR base station

GPRS General Packet Radio Service

GPS Global Positioning System

GTP GPRS Tunneling Protocol

ID Identity number

KPI Key Performance Indicator

LA Link Adaptation

LoS Line Of Sight

LT Luby Transform

LTE Long Term Evolution

MAC Medium Access Control

MBB Mobile Broadband

MC Multi-Connectivity

MCG Master Cell Group

MCM Multipath Channel Margin

MCS Modulation and Coding

Scheme

MRS Mobility Reference Signals

NAS Non-access stratum

NG Next generation

NLoS Non Line Of Sight

NR New Radio

PDCP Packet Data Convergence

Protocol

PDU Protocol Data Unit

PE Power Efficient

PHY Physical layer

PLCP Physical Layer Convergence

Procedure

PLM Path Loss Margin

PSS Primary Synchronization

Signal

QoE Quality of Experience

QoS Quality of Service

RA Random Access

RACH Random Access Procedure

RAN Radio access network

RAT Radio Access Technology

RF Radio Frequency

RLC Radio link Control

RRC Radio resource control

RRM Radio Resource Management

RS Reference Signal

RSSI Received Signal Strength

Indicator

SBH Self-backhaul

SCG Secondary Cell Group

SDN Software defined Network

SGW Serving Gateway

SS Synchronization Signal

SSS Secondary Synchronization

Signal

TAI Tracking Are Identifier

TCP Transmission Control Protocol

TM Transmission Mode

TRP Transmission reception point

TTI Transmission Time Interval

UDP User Datagram Protocol

UE User Equipment

UL Uplink

UP User Plane

UTRAN UMTS Terrestrial Radio

Access Network

VA Virtual Access Point

WLAN Wireless Local Ara Network

WT WLAN Termination

xMBB Extreme Mobile Broadband

Xn Inter-node interface

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1 Introduction

The expectations on performance towards future 5G systems lead to giving attention to

high-frequency bands, specifically, so-called mm-waves whose frequencies are defined

between 6 GHz and 100 GHz in mmMAGIC 1. The range of use cases envisioned for

the new generation of communication system, has expanded way beyond voice and

mobile broadband applications. Designing new system (or planning an evolution)

comes across various levels; starting from propagation analysis through various

network layers and up to end-user applications. In this document, we are pointing at

envisioned mandatory architectural elements (architectural enablers) for mm-wave

RATs, working in frequency bands from 6 GHz to 100 GHz and integrated with other

new and legacy technologies.

There have been use case families envisioned for 5G [NGMN15][Nok15], but during

3GPP standardization process the use cases belonging to extreme mobile broadband

(xMBB) gained the highest prioritization (also called enhanced mobile broadband,

eMBB in 3GPP). In xMBB use cases defined in [MMMAG15-D11], such as “media on

demand”, “cloud services”, “immersive early 5G experience” and “smart office”, both

high connection density and high data rates are the challenges to be addressed from

the RAN architecture perspective. In this white paper we present several architectural

enablers which are specific for the mm-wave RAT, and we complement them with

optional technology components and RAN functions. The connection density, traffic

density and data rate challenges are to a large extent handled by densification of the

network, and mm-wave self-backhauling is a key enabler for cost-efficient ultra-dense

deployments. Another enabler helping to cope with these challenges is low-band

integration e.g. help propagate control signalling and to speed-up initial access. A high

number of connections can bring challenging episodes of intense control signalling—

this is mitigated with new, intermediate mobility state RRC_INACTIVE.

Apart from new architectural solutions developed for 5G we need to integrate mm-

wave system with other RATs, primarily for reliability reasons. Integration of mm-

wave systems with LTE using multi-connectivity gives the opportunity to provide

more reliable control signalling and faster initial access in beam-based RAN.

1 Strict definition of mm-wave bands include frequencies between 30 and 300 GHz, but the industry often use a

looser definition including any frequency above 10 GHz. In mmMAGIC project the mm-wave range is referring to

even larger range of frequencies: from 6 to 100GHz

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2 Generic Architecture

Figure 2-1 Generic mm-wave system architecture diagram - RAN perspective

The 5G network architecture shown in Figure 2-1, is expected to consist several RAN

entities. The RAN entities will in-turn comprise existing LTE eNBs (evolved NodeBs),

as well as access points (APs) supporting the next generation RAT, denoted “New

Radio” (NR), which will be capable of supporting mm-wave frequencies. The name for

the NR APs has recently been coined as “gNB” [3GPP TR 38.801]. A brief description of

the various 5G architecture elements such as gNB, Next Generation Core network and

Interfaces are described in this section.

gNB

The gNB is an enhanced version of the LTE Rel-13 eNB, which will be capable of

supporting low and high frequency bands. Whilst the full set of existing features and

functions supported by this entity can be obtained from [3GPP TS 36.401]; some of its

distinguishing features are: facility to support network slicing, tight interworking with

E-UTRAN, capability to support multi-connectivity, session management, and its

ability to support existing and new interfaces. Additionally, it is worthwhile to

mention that the gNB in 5G systems can be expected to include one or more

transmission/reception points (TRPs),Some gNB functionalities can be distributed

across different TRPs, while others are centralized, leaving the flexibility and scope for

specific deployments to fulfil the requirements for specific use cases.

Next Generation Core Network (NG-CN)

The NG-CN must be capable of supporting CP signalling towards the LTE and NR

APs. Here, it is important for the NG-CN to store the UE context for both the LTE and

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NR APs. To maintain mobility between different access networks, the NG-CN will be

in-charge of establishing and retaining the inter-CN signalling. It will also be in-charge

of supporting mobility features like, tracking area list management, UE time zone and

location mapping. UE reachability in Idle mode, QoS and session management are the

other features that must be supported. Additionally, the feature of service flow

management and user gateway support functionality will also be included.

Interfaces

With enhancements in the functional blocks, the interfaces must be capable of

establishing logical connections with several APs tailored to different technological

systems. From the view point of 5G access points, two main interfaces shall be

introduced: NG and Xn interface. The NG interface shall be open and must support the

exchange of signalling information between the 5G-RAN and NG-CN. Whilst, the Xn

interface must offer logical connectivity between eNB and gNB. The NG interface must

be capable of supporting CP and UP separation, at the same time have separate radio

network and transport layer specifications. While on the other hand, the Xn interface

must support the exchange of signalling information and data forwarding between the

endpoints and gNBs. Lastly, the NG interface must be capable of carrying interface

management, UE connect and mobility management functions; in addition to the

enhanced features to support the transportation of NAS messages, paging and PDU

session management. One rule applicable to both cases, is that they must be future

proof to fulfil diverse requirements, services, features, and functionality.

Specifically, for the 5G mm-wave RATs both standalone and non-standalone should be

supported, i.e. mm-wave RAT should be fully operational without support of other

RATs (standalone deployment); however, mm-wave RAT must be benefitted from

tight integration with other RATs (typically low-band systems with better coverage

properties), e.g. improved initial access or improved reliability due to usage of multi-

connectivity with low-band system such as LTE.

3 Vertical Multi-RAT/RAN management

The management of several RATs in a heterogeneous multi-RAT network involves the

use of dedicated Key Performance Indicator (KPI) to switch from one technology to

another one, following dedicated criteria (power efficiency, flexible QoS, multiple

Access Point (AP) connection to send and receive the data) and the integration in

multi-RAT architectures. The generic architecture described in Section 2, encompasses

gNBs as well as eNBs that require multi-RAT management to perform mm-wave and

LTE-A carrier aggregation. The control-plane may then forward the metric decision

evaluated at the PHY layers to the gNB or eNB and the decision is then activated to

achieve data transport between communication entities. For that purpose, dedicated

link adaptation metrics in charge of air interface and transmission mode (TM) selection

have to be designed, evaluated and forwarded in the multi-RAT management engine

followed by integration in the generic architectures detailed in this paper.

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3.1 Multi-RAT multi-layer management

The multi-RAT/RAN management resorts from a vertical multi-layer management of

interfaces and TMs depending on involved technologies in the RATs management

[SVG+16][SUMP16] and optimization criteria (power and spectral efficiency, radio

coverage, etc..). It may cover three independent abstraction layers, where the activated

abstraction layer depends on functional blocks that are required to change the air

interface and TMs to perform the transmission between the two communication

entities.

Link adaptation metrics are the input of the multi-RAT/RAN management processing

in order to choose and activate the appropriate air interface and transmission mode,

depending on propagation conditions and optimization criteria. The green link budget

(GLB) metric [SUM16] is the candidate link adaptation metric for power efficiency

optimization in the multi-RAT context where independent interfaces may be

considered to carry out the transmission. The GLB metric allows a link budget based

comparison between interfaces exhibiting independent power sensitivity levels and

different radio frequency spectrum operations. Innovative KPIs and multi-radio

interface engine as recently introduced in the ETSI Reconfigurable Radio System (ETSI

RRS) technical committee, are computed at the lowest layer, typically at the PHY layer

based on Received Signal Strength Indicator (RSSI) and link budget elements deduced

from involved interfaces in the multi-RAT process.

Figure 3-1 illustrates the architecture using 5G RAT link adaptation metrics to select the

most appropriate technology (technology 1, 2 or 3 following a generic approach), to

establish communications between the transmitter and the receiver. Link adaptation

(LA) metrics are computed using available PHY parameters as the RSSI and context

information provided by Physical Layer Convergence Procedure (PLCP) headers and

signalling headers of every concerned RAT. Metrics are then forwarded to the

appropriate layer to initiate air interface switching. The selection is done considering

equivalent throughput schemes in accordance with the transported services [SUM16].

The power efficient link adaptation metric adopted in mmMAGIC to optimize power

and cost efficiency is described in [SUM16], exhibiting important transmit radiated

power gains for mm-wave and Wi-Fi hot spot deployments [mm-MAGIC D3.1,16]. To

transport decision, the existing X2-S1 and Uu interfaces are differently exploited,

depending on emulated abstraction layer activation.

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Figure 3-1 Generic multi-layer architecture using 5G RAT link adaptation metrics for multiple RAT management

Depending on involved technologies in the multi-RAT scenario, each layer is able to

manage interfaces having their own capabilities to exchange context information

together.

The abstraction layer 1 exploits PHY and MAC protocols to exchange information and

forward the radio interface engine decision. Switching from one Modulation and

Coding Scheme (MCS) to another in a single RAT may be possible in this

configuration. A switching between IEEE802.11 ac TMs and IEEE802.11 ad TMs may be

also implemented using the fast session transfer protocol designed in the IEEE802.11

ad standard.

The abstraction layer-2 requires a L2.5 layer to manage the independent interfaces that

do not benefit of a common context information exchange. The I-MAC layer [KBN12]

which was designed in the ICT-FP7 OMEGA project, illustrates a concrete hardware

and software implementation for indoor communications.

The abstraction layer-3 utilises typically the generic architecture exposed in section 2

with control and data plane architectures using S and X1 interfaces to carry out multi-

RAT carrier aggregation. An illustration of multi-RAT abstraction layer-3 is detailed in

[SUMP16] embracing mm-wave components in innovative control and user plane

splitting schemes . The adaptor represented in Figure 3-1 is similar to the “WT” (WLAN

Termination) specified in 3GPP Release 13 for LTE/WLAN RAN-level aggregation. The

same GTP-U tunnelling is then utilized for data splitting.

4 Architectural enablers

4.1 Multi-connectivity

A widely acknowledged limitation of mm-wave systems is the increased path-loss

associated with the higher carrier frequencies [MMMAG16-D21]. Because of this, mm-

5G R

AT L

A m

etri

cs, R

RM

and

NM

met

rics

Abstraction layer-2

Abstraction layer-1

Abstraction layer-3

5G RAT LA metrics computation and feedback

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wave NR cannot be relied upon to provide ubiquitous coverage from a single

transmission point. Mm-wave often has to provide line-of-sight (LOS) between the

access point and UE, which can frequently be prone to blocking and fast fading.

However, the strict 5G requirements on e.g. throughput will necessitate the use of the

wider bands available at mm-wave frequencies. To address the coverage issues, mm-

wave NR need to support multi-connectivity where a UE can be connected to multiple

nodes at once to facilitate either aggregation of carriers for increased throughput, fast

switching between nodes to enable seamless mobility, or redundant transmission

schemes where the same information is sent over multiple link to increase the

reliability.

In LTE Rel-12 there were two options for dual connectivity (DC): 1A (MCG and SCG

bearer) and 3C (MCG-split bearer). In [MMMAG16-D31] we proposed that these

options should be used for mm-wave NR. In addition, we introduced an alternative,

namely SCG-split bearer which allows the user plane (UP) traffic to be sent over both

links (similar to MCG-split bearer), without straining the processing capacity of the

master node.

Figure 4-1 Multi-connectivity bearer options.

The proposed dual connectivity concept is a mandatory solution for the network

design, in order to provide sufficient reliability for standalone mm-wave NR and to

leverage on LTE coverage for non-standalone deployments. Which of the three options

to use is a matter of optimization, and recently began to be discussed in 3GPP NR

Study Item and are now part of [3GPP TR 38.801].

Another extension of the DC concept, is the possibility to add additional cell groups

beyond the master cell group (MCG) and the secondary cell group (SCG), also known

as a multi-connectivity (MC). The complexity of balancing the load between multiple

links will increase significantly compared to DC, but there are benefits to have a

preconfigured backup link with redundant coverage. This will allow a quick handover

in case of radio link failure on any of the initial links and will be especially useful for

standalone mm-wave NR. The proposed 5G node, known as “gNB” will support both

distributed and centralized deployments, where multiple transmission/reception

points (TRPs) contain a configurable part of the protocol stack. This can provide

pooling gains with centralized functionalities, for instance mobility handling or

scheduling decisions, resulting in more demanding requirements on the backhaul in

terms of e.g. capacity and synchronization. The deployment of the TRPs should

provide some level of redundant coverage to enable this.

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Yet another proposal is control plane (CP) multi-connectivity, also known as RRC

diversity. This was studied for LTE Rel-12 [3GPP TR 36.842] and is considered by

mmMAGIC, given that it will play an important role in a mm-wave system, especially

for standalone mm-wave case. In LTE, the RRC signal is always transmitted directly

from the master eNB (MeNB) to the UE, even for signalling related to the secondary

eNB (SeNB). With RRC diversity, part of the RRC message, or the entire RRC message

can be sent via the primary link, the secondary links, or both. This allows for improved

reliability using redundant messages, or reduced latency by transmitting independent

messages related to the secondary node directly from the SeNB to the UE. However, an

important aspect when considering RRC diversity will be how to handle race

conditions, when multiple, contradicting, RRC messages are received via different

links. The RRC diversity solution can be seen as optional feature for mm-wave NR

which can increase the reliability at mm-wave frequencies.

Since it will be challenging to provide ubiquitous mm-wave coverage with a

reasonable deployment density it will be imperative to supplement the connectivity

with low frequency support. As the mm-wave NR will initially be deployed in many

areas already serviced by LTE, it will be beneficial to leverage on the incumbent

installations and support a gradual deployment of mm-wave NR. By harmonizing the

protocol stacks of LTE and NR, it will be possible to have a tight interworking

between LTE and NR which will for instance, enable aggregation of carriers or fast

switching between the RATs, proposed in mmMAGIC [MMM16-D31]. Work has since

begun in 3GPP to support the interworking between LTE (and its future releases) and

NR (which will operate in both low frequencies and mm-wave frequencies) [3GPP

TR.38.801].

Initial simulation results show that by co-deploying LTE at 2.6 GHz and NR at 15 GHz

in a dense urban environment with DC capabilities, it will provide synergy effects

greater than the sum of the capacity of either RATs as can be seen in Figure 4-2.

Figure 4-2 Downlink performance for LTE-NR interworking.

A similar evaluation comparing LTE DC at 2.6 GHz with LTE-NR DC at 2.6 and 28

GHz respectively show that the mm-wave RAT improves the median throughput by

up to 17 times at high loads and between 1.5 and 2 times for the 5th percentile

throughput.

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4.2 New mobility state: RRC_INACTIVE

In [MMMAGIC16-D31] it was proposed to introduce a new RRC state to complement

the existing states, RRC_IDLE and RRC_CONNECTED. The new state is referred to as

RRC_INACTIVE and allows a UE to benefit from several aspects of the two original

states. Similar to RRC_IDLE, the UE would perform cell-reselection based on

measurements of reference signals without providing the network with measurement

reports. Additionally, when the network needs to reach the UE, e.g. when DL traffic

has arrived, the network pages the UE which in turn performs a random access (RA) to

connect to the network. Likewise, when the UE needs to initiate UL traffic, it performs

a RA to the current cell to synchronize and connect to the network. What differs for

RRC_INACTIVE compared to RRC_IDLE is that the UE and gNB maintains

configurations obtained in RRC_CONNECTED related to e.g. AS context, security, and

radio bearers so that after the RA, the UE can resume its old configurations without

much delay. In addition, the gNB can maintain the CN/RAN interface (NG-C and NG-

U), further reducing the resumption latency. Since the UE resumption from

RRC_INACTIVE to RRC_CONNECTED assumes that the old UE context can be

reused, whichever cell the UE has re-selected must be able to retrieve the context from

the old cell. If the context fetch fails, the network can instruct the UE to perform a RRC

Connection Setup similar to the one performed from RRC_IDLE.

Figure 4-3: State transition diagram

Since the RAN/CN connection can be maintained in RRC_INACTIVE; the CN will

assume that the UE is in ECM_CONNECTED. Whenever the network needs to reach

the UE, e.g. when there is DL data available, the network will need to page the UE, as

the RRC connection is suspended. However, as the CN assumes that the UE is in

connected mode, the CN cannot initiate the page, but rather the RAN will have to

initiate the notification. To facilitate a more efficient paging scheme, the RAN can

assign a limited area, covering one or more cells, within which the UE can be paged by

the RAN. While the UE moves within this RAN area it does not need to notify the

network of its location. It is only when the UE moves outside the RAN area that it will

have to signal the network of its new location and be assigned a modified RAN area.

As the RAN notification area can be smaller than the CN Tracking Area, the RAN

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paging message can be sent out in a smaller number of cells than a typical CN paging.

This can also be used in conjunction with the Smart Paging procedures introduced in

LTE Rel-13, where the UE reports its previously visited cells and time spent in these

cells. This information can be used for statistical analysis to estimate a probable

location of the UE (e.g. a stationary UE could be paged in only from its previous cell).

4.3 Mm-wave cell clustering

In mm-wave communication it is challenging to provide continuous connectivity for

the active user in dynamic environment especially due to changing position of the UE

and other objects in the scene. In case of such beam-based prone to obstruction links, it

is crucial to provide mechanism that can handle switching the serving cells in quick

and transparent manner to CN. The mm-wave node clustering is therefore mandatory

element of the network architecture. Detailed mm-wave cell clustering description has

been provided in [D.31] and previous white paper [MMMAG16-WP31]. Here, we focus

on architectural enablers related to mm-wave cell clustering.

The layout and architecture of the cluster will depend on the quality of backhaul and

coverage of the different nodes. If the backhaul is ideal with very low latency, the

cluster can be coordinated by a central node, handling all scheduling between the

nodes, deployed with a non-ideal backhaul, which may preclude a central scheduler.

Instead, in such cases each node is responsible for the lower layers (MAC and PHY),

and can relay packets through an evolved RLC layer to other nodes when a UE needs

to switch APs. In the cluster one AP with the sufficient processing power and CN

connection quality to support the cluster, will coordinate the mobility within the

cluster. This implies provision of CN connection to that APs that allows flexible

formulation of clusters and ensuring that each mm-wave node can a part of valid

cluster.

To ensure connectivity within the cluster, it may be necessary to rely on the wide area

coverage of low-frequency RATs, e.g. LTE-A, when the mm-wave RAT has limited

reliability e.g. due to signal blockage. The lower frequency can then relay traffic and

control signals from the CH to the UE, and assist in intra-cluster mobility. This makes

strong connection between inter-frequency multi-connectivity and mm-wave

clustering.

Additionally, the mm-wave access clustering is expected to work even with wireless

self-backhauling, where the nodes may relay traffic using the mm-wave air interface.

However, this may introduce additional latencies in the system which needs to be

considered.

4.4 Network slicing

Network slicing will be an important aspect of 5G networks, where multiple services

and business operations can be realized independently on a shared infrastructure

(including shared processing, storage, transport, radio spectrum, and hardware

platforms). This will allow for a more cost- and energy-efficient asset utilization where

the logical separation allows for a flexible and independent configuration and

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management of slices without compromising stability and security. However, it is

important that the configuration and maintenance of the slices add a minimum

overhead as not to waste scarce RAN resources. It should be possible for an operator to

configure a specific slice with a customized logical network optimized for a specific use

case while still not preventing the operation of other slices. Even though a slice may be

optimized for a single use case, the notion of network slicing should not be confused

with the concept of different services. It is possible that a single slice supports multiple

services with e.g. differing numerologies or KPIs, and it is likely that multiple slices on

the same network provide the same service, e.g. multiple operator offer mobile

broadband (MBB) services with independent logical networks on the same physical

infrastructure.

Since different network slices are to be operated as independent networks, it is

important to ensure slice protection to prevent shortage of shared resources, (e.g.

common signalling resources). This could be achieved using slice specific access class

barring where the network configures UEs already associated to a specific slice with

e.g. modified back-off timers.

To facilitate an optimized slice selection, a UE can provide the network with a

configured slice ID, which is obtained after its initial attach. On the absence of a valid

slice ID, the UE should access using default configurations and the network will

configure and redirect the UE to a proper slice.

4.5 Self-backhauling

The new level of densification in 5G will require innovative approaches in radio

resource, mobility, and/or interference management. A centralized operation of mobile

networks, as implemented by C-RAN, allows for obtaining a globalized view on

mobility and interference management in order to optimize the resource usage

[BDO+13]. Aiming at centralization of the mobile network operation; high capacity

links among access points of small cells and the centralized base station of macro cell

are required, which is usually satisfied by optical fibre connections. Nevertheless, it

may be too expensive or impractical to equip every cell with fibre connectivity. As an

attractive, cost efficient alternative, wireless backhauling enables direct, low latency

connections amongst access points and base stations and, hence provide them with a

possibility for enhanced cooperation to achieve better performance, in addition to

providing high data rate throughput to small cells.

A further step of wireless backhauling is self-backhauling, which refers to a set of

solutions to provide technology- and topology-dependent coverage extension and

capacity expansion utilizing same frequency band for both backhaul and access links,

as shown in Figure 4-4. Self-backhauling provides an efficient way to combat

infrastructure constraints especially in dense network deployment, where access to

fibre may be limited to only some APs. However, over time as the fixed infrastructure

will become more available, the self-backhauling will gradually evolve.

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Figure 4-4 Concept of self-backhauling.

The dynamics and self-autonomy of self-backhauling solutions can gradually evolve

into Software Defined Networking (SDN)-based solutions, where one logical controller

is supposed to monitor topology changes, node-to-node radio channel status and all

the traffic needs in a real-time manner. In this case, backhaul networking for densely

deployed small cells could be characterized by a ringed-tree topology with multiple

backhaul links per node and different levels of backhaul links [SGV+16]. An example of

a ringed-tree backhaul networking is illustrated in Figure 4-5.

Figure 4-5 An example of ringed-tree self-backhauling.

As shown in the Figure 4-5, a network node can have more than one backhaul link, and

vertical links would have higher priorities in route selections than horizontal ones.

Focusing on this backhaul networking, a high-level radio resource management

procedure is considered as follows

1. Start-up configuration: Each network node decides if its backhaul links should

be always-active or improvised, e.g., for high-level vertical backhaul links, they

may be always-active, where other candidate backhaul links are improvised to

reduce the signaling overhead of all on the scenario. Furthermore, radio

measurement procedure and reference signal sounding are configured, and

maximum number of simultaneous backhaul links (dependent on RF chains)

for a specific node are specified.

2. AP side configuration: channel measurement for each possible backhaul link,

and reporting the channel state information to the controller. Reporting

bandwidth demands for access and backhaul respectively are also included.

Core

Network

Self-Backhauled Node

Node with

dedicated backhaul

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3. Controller side procedure: end-to-end routing procedure to form backhaul

networking for a cluster of nodes, plus routing policy broadcasting and radio

resource allocation.

5 RAN functions and network integration

5.1 RAN functions

5.1.1 Power efficiency oriented KPIs

A power efficient link adaptation metric has been designed [SUM16] to perform

dynamic multi-RAT management under power and cost efficiency criteria

guaranteeing QoS and radio coverage. This metric, denoted Green Link Budget (GLB)

metric, carries out a selection of the most power efficient transmission mode and air

interface by computing two normalized sub-metrics, the and sub-metric. The -

metric covers extra power requirements to guarantee QoS on a given transmission

mode when passing from AWGN to multi-path propagation conditions i.e. the

Multipath Channel Margin, (MCM) and the extra required radiated power i.e. the Path-

Loss Margin (PLM)), which is necessary to have a received power level equivalent to a

free space path-loss situation. The selected TMs are associated with the minimum

sub-metric values of concerned interfaces. The-metric computes the difference

between the received power and the required power for the transmission mode

initially selected by the -metric. A power control is then done by the use of

numerical-metric value to adjust and limit the Emitted Isotropic Radiated Power

(EIRP) at the AP or the gNB in small or macro-cell deployment.

Figure 5-1 Multipath Channel Margin (left) and Path Loss Margin (PLM) metrics visual interpretation

Figure 5-1 gives the definition of the -metric. MCM is derived from link level

performance in a multipath versus AWGN case for a given TM and technology

1E-6

1E-5

1E-4

1E-3

1E-2

1E-1

1E+0

0 5 10

BE

R

SNR

MCM

AWGN

Multipath

Channel

70

75

80

85

20 21 22 23 24 25 26 27 28 29 30

Pro

pag

atio

n L

oss

(dB

)

distance d (m)

PLM

Free space path-loss

Multipath path-loss

α = MCM + PLM

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delivering the desired throughput to transmit data with a QoS translated in a Bit Error

Rate target. PLM is the variation of measured RSSI and an idealistic RSSI linked to free

space path-loss without any obstacles.

The GLB metric has been applied upon the mm-MAGIC multi-band system integration

model in which each interface is enabling to operate upon several RF bands

[MMMAG17-D13]. The GLB metric is then in charge of selecting the most power

efficient RF band in connection with the environment to establish radio communication

and available technologies in the multi-RAT scenario. Another application is the access

point selection to perform communications in multi-RAT handover scenarios. The

metric has been also integrated in radio engineering tools in order to optimize inter-cell

distance for 5G multi-RAT/RAN deployment [UMS15] [MMMAG17-D13].

5.1.2 Transport layer optimization to improve mobility

mm-wave signals are more outage-prone compared to low-frequency carriers;

blockage can be induced by trees, street furniture, transport traffic and even human

body. Signal blockage (in either control or data channel) may lead to an abrupt

reduction in link quality or to Radio Link Failures (RLFs) with drastic impacts on

transport layer control protocols (e.g., TCP) resulting in degraded quality of experience

(QoE) for end-users. In the context of mm-wave RAN, signal outages or RLFs are not

only triggered in cell boundaries in case of high mobility, but also in any locations

within the coverage area of a mm-wave AP as soon as the strong LOS or reflection

channel component is blocked by dynamics of environment (even if the UE is

stationary).

One way to remedy the QoE from user perspective is to apply efficient forward error

correction (FEC) schemes, known as Fountain codes to counterbalance the outage

impacts. Fountain codes have been designed for lossy and varying channels with

erasures. Luby transform codes (LT codes) are the first class of universal erasure codes

out of them [MLU02]. The source for fountain codes will encode a file into streams of

packets, each containing random parts of the original file. The fountain source keeps

sending these encoded packets to the destination, without knowing which packets will

be received. At the receiver’s side, when the number of packets received is slightly

higher than the original file size, the source file can be recovered. Combining such FEC

schemes at application level, facilitates utilising simpler transport protocols (e.g. UDP)

without congestion management or error check / control at transport layer. This in-turn

can additionally improve user QoE by avoiding unintended cross-layer interactions

when facing abrupt link quality changes (particularly, in mm-wave bands) as outlined.

Figure 5-2 Sequence number per file received over time for TCP (left) vs. LT (right)

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Our simulation analysis in equivalent settings suggests that LT codes can achieve

complete and reliable file transmissions over UDP with lower levels of overhead (i.e.

better throughput) in mm-wave bands (as shown in the figure above- right hand side).

The red line depicts completion of each file (52 MB) in sequence. Furthermore, analysis

also shows that in outage regime (of mm-wave bands) application on top of TCP barely

receives all the packets transmitted out of each file as a large number of them are lost

during the outages (as in the figure above- left hand side). On the contrary, LT (over

UDP) provides complete file deliveries thanks to forward error correction mechanism,

resulting in more consistent QoE.

5.1.3 Reference signal design to allow active mode mobility in a

beam based RAN

As the mm-wave access will need to rely on beam-formed connectivity to provide

connectivity, coverage, and capacity to the UEs due to the increased path loss at higher

frequencies, the mobility procedures need to be adapted to cope with this. In LTE, the

mobility related measurements were based on periodic reference signals, transmitted

omni-directionally by cells. If a UE was in RRC_IDLE state, it would select the best cell

to camp on and if the UE were in RRC_CONNECTED, then the UE would send a

measurement report to the network, if the signals surpassed certain network

configured threshold, and the network would select the target cell for handover. For

NR, it has been agreed that there will be two levels of mobility, with and without RRC

involvement. Mobility without RRC involvement will be limited to scenarios where the

mobility is between transmission/reception points (TRPs) belonging to the same gNB,

where tight synchronization can be assumed. In these cases, beam management

procedures, similar to intra-gNB procedures utilizing channel state information

reference signals (CSI-RS) will suffice. To cater to the wide range of mobility

requirement of the 5G use cases, the network will be able to configure the periodicity of

the CSI-RS from a few milliseconds up to several seconds, or turn off completely, if

there are no UEs active in the cell.

However, as tight synchronization between nodes cannot be assumed to be ubiquitous,

an asynchronous mobility procedure is needed which is provided by the RRC based

mobility. These mobility reference signals (MRS) will need to contain a synchronization

signal (SS) as well as a beam identifier (BRS (beam reference signal)) for the UE to be

able to distinguish beams with different synchronization (e.g. from different nodes).

The active mode mobility in NR requires frequent transmissions of reference signals in

narrow beams to ensure prompt switching in case of poor coverage. However, if these

reference signals were provided in every beam with the strictest periodicity required,

the overhead and added interference would be prohibitive, not to mention the wasted

energy in transmitting superfluous signals not used by the UE. Thus, unlike LTE, there

is a need to distinguish between idle mode and active mode mobility. The requirement

for the idle mode mobility is to provide means for accessing the network, which is

much more latency tolerant than the active mode mobility where e.g. using a

periodicity of 100 ms would be acceptable compared to 5-10 ms for high speed user

during active mode mobility.

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5.1.4 Low frequency assisted initial access beam training

The initial access process comprises the three tasks of downlink timing and frequency

synchronization, system information acquisition and uplink timing synchronization.

During initial access a UE has to establish a RRC connection with the corresponding

mm-wave AP. The performance of this procedure directly impacts the user experience.

Therefore, on PHY layer a beam alignment must be achieved within short time.

Exploitation of the limited a-priori information on the preferred transmission direction

at both ends of the link will support this. In a non-standalone deployment, i.e., a

heterogeneous network, where mm-wave small cells are located within the coverage

area of a macro cell operating at low frequency, low frequency RAT assistance can

improve initial access performance significantly. Especially UE power consumption

and latency can be reduced.

In the following, the three mentioned tasks of low frequency RAT assistance are

highlighted.

5.1.4.1 Downlink synchronization

For downlink synchronization the UE exploits synchronization signals transmitted by

the AP. These are in particular time-frequency resources with a certain periodicity,

which allow acquisition of symbol, slot and sub-frame timing. After achieving that, the

UE is able to obtain the cell ID. If the UE is located in a low frequency RAT coverage

area, the low frequency RAT can transmit information about frequency and cell IDs of

mm-wave small cells within its coverage area. With this signalling, the UE does not

need to perform an exhaustive search over the whole small cell ID space, but it only

tries to detect the signalled cell IDs. As a consequence, the UE power consumption for

downlink synchronization is significantly reduced.

5.1.4.2 System information transmission

The second task of the initial access procedure is to acquire the system information

which provides all the essential information for accessing the network to the UE. The

coverage of the system information determines the coverage of the cell. Some of the

system information components, e.g. the system frame number, are changing fast on

the basis of one or several mm-wave RAT frames. Other system information

components vary relatively slowly, so information about system bandwidth, random

access resources, paging resources and scheduling of other system information

components is typically semi-static. For this reason, it can be energy efficient to convey

some of the slowly varying system information by exploiting the existing low

frequency RAT. The fast changing system information components, however, need to

be transmitted by the mm-wave RAT.

5.1.4.3 Uplink synchronization

It is important that efficient uplink (UL) data transmission in the mm-wave RAT is

supported as well, especially for “UL data traffic dominant” use cases, e.g., uploading

content, such as high-resolution videos to social media during sports events, concerts

etc. UL synchronization needs to be achieved prior to any UL packet transmission to

ensure that all the co-scheduled UEs’ UL signals are time-aligned at the eNB. A RACH

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procedure, similar to that standardized in LTE can be used. Based on the RACH

preamble transmitted by the UE, the eNB can determine the timing advance value for

the UE. The radio resources for the preamble transmission are typically part of the

system information and such system information can be signalled by the low

frequency RAT. This can be viewed as a basic assistance to the UL synchronization. To

ensure a certain UL preamble coverage, if several preamble formats are supported by

the system, the low frequency RAT can signal a particular preamble format to the UE

in order to realize the network assisted preamble format selection. In case of contention

free RACH, the low frequency RAT can signal the exact preamble sequence to be used

by the UE.

During the LTE-like RACH procedure, the RACH response signal can be also

transmitted by the low frequency RAT. In addition to the above mentioned options for

UL synchronization assistance, the low frequency RAT may also offer assistance to the

possible beam alignment operations during the initial UL synchronization procedure.

5.1.5 User movement prediction

Good propagation conditions and beam steering are necessary to achieve high data

rates. In order to achieve this, accurate position estimation and position tracking is

needed, especially for dense urban and high mobility scenarios. This poses a number of

challenges related to the capability of accurately estimating the position and following

the movement of the users, in order to maintain a stable mm-wave connection. Also,

the beam-training overhead per user is independent of the one related to other users

and depends only on the user’s mobility. As the number of users increases, so does the

beam training overhead. In high density mobile scenarios, this overhead may become

prohibitively large, unless more intelligent beam-training strategies are used. From this

perspective, mobility and user density are equivalent issues to be tackled by beam

training and tracking algorithms, and special care is required when highly mobile

users associate to APs that already serve a large number of mm-wave terminals. In

particular, these scenarios yield three related issues: first, beam training procedures

upon AP association can be too slow and result in suboptimal beam pattern choices,

which in turn would lead to unstable channel and data rates; second, the changes of

the optimal beam pattern induced by the movement of the users must be tracked in

order to consistently maintain a sufficiently high link rate; third, links can be easily

broken due to the users moving behind an obstacle or some blocking material, such as

a building, vegetation, vehicles, or other users. In these cases, agile, possibly proactive

AP re-association mechanisms should be provided, in order to avoid that a user loses

connectivity over long time periods, and a complete beam training procedure needs to

be re-initiated from scratch.

Embedding history information about the users’ movement patterns into the beam

training and tracking process at mm-wave AP can considerably improve the

performance of mm-wave links and relieve part of the time burden caused by beam

training procedures [PDW17]. The prediction of the movement of the users can be fully

estimated at the AP side, without requiring any explicit feedback of position

information from the users to the AP. This yields the two-fold advantage that it incurs

no overhead, and that no interface is required between mm-wave communication

systems and other positioning subsystems embedded in user terminals or vehicles,

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such as Global Positioning System (GPS) receivers. In fact, no precise location

information is required from external sources: the same can be reliably estimated by

APs, using only some information from current beam pattern choices that would help

drive future beam tracking procedures.

5.1.6 User localization and environment mapping to improve

mobility

mm-wave technology will play an essential role in indoor localization and mobility

because of its unique characteristics. Propagation occurs in quasi-optical patterns,

whereby reflections off the boundaries of indoor surfaces and obstacles are subject to

limited scattering and the line-of-sight (LoS) component tends to be predominant over

non-LoS (NLoS) components even in the presence of obstacles. Mm-wave signals are

characterized by short wavelength and large bandwidth, thus even directional

transmission may generate multiple reflected paths reaching the moving receiver with

different delays and angles of arrival (AoAs). The information extracted by the phased

antenna arrays typically used for mm-wave devices fits well with the purpose of

localization. In a generic environment where different mm-wave APs are present, the

signals transmitted by each AP typically reach a node via both LoS and NLoS paths.

The antenna array of the node can be used to estimate the AoA of each multipath

arrival from each AP, thereby providing a so-called AoA spectrum for each AP that

illuminates the node. The AoA spectrum information can be directly passed on by a

node’s receiving hardware, or can be derived by processing beam tracking information

(i.e., the sector ID of the phased antenna array). The latter can be forwarded by MAC

protocols such as 802.11ad, which are aware of the sector ID. The algorithm estimates

the location a mobile user in an indoor space working without any a priori knowledge

about the surrounding and the location and number of access points available

[PCW17]. Once the user location and the anchors have been estimated with sufficient

accuracy, it is possible to reconstruct the shape of environment determining the

location of reflective surfaces and walls. The intuition is as follows : the geometric

relationship between physical APs and virtual APs (VAs) permits to estimate the

location of the point on the wall where the signal of the physical AP reflects. The

accuracy of the estimation is enhanced taking into account different user locations to

see the reflection point on the wall from different angles. Accurate localization and

tracking can also serve as a proxy for physical communication functions, such as

beamforming, handovers and context switching.

In Section 3.4 baseline architecture for the mm-wave AP clustering was described, in

this section we extend it to support localization function. To optimize the cluster

management, it could be beneficial to consider the extent of UE mobility and

implement location information and heuristics to predict when and where a UE should

perform handover; considering link quality and the overhead associated with the

handover. Additionally, as the mm-wave RAT will be heavily reliant on beam-based

transmission, the beam training and beam width adaptation strategies need to be

evaluated to optimize the handover procedure for various mobility scenarios. As some

of the APs within a cluster may be serving multiple UEs using overlapping beams will

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be beneficial to coordinate the beam steering between the APs based on network

statistics, to minimize the beam interference. Therefore, clustering might introduce

new, optional RAN functions such as UE location tracking and mobility event

prediction entity.

5.2 Network integration

In the previous sections, five architectural enablers for mm-wave system were

identified as: multi-connectivity, new mobility state, mm-wave cell clustering, network

slicing, and self-backhauling. To design architecture for such a system it is necessary to

understand relation between the enablers and integrate system in the way that all these

relations are managed. The multi-connectivity concept is related to mm-wave cell

clustering where UE is primarily using one active connection to mm-wave AP, but

simultaneous connectivity to the low-band system might be highly beneficial to

properly distribute control signalling from the CN. Additionally, the way how the UE

handles cluster of mm-wave APs has much in common in maintaining APs used in

multi-connectivity. If network slicing is supported, the UE will be configured to use

and be served on a given slice, thus the UE will be able to continue performing multi-

connectivity or connecting to the different mm-wave cell clustering using the

configured slice. At the network side, coordination will be needed between the master

and the secondary nodes in order to server the UE on the same slice. The same slice

need to be supported by both nodes in order to perform dual connectivity.

The mm-wave cell clustering is also heavily dependent on available backhaul -

performance of backhaul connection implies possible architectures in mm-wave

cluster, i.e. better the backhaul connection, the more centralized the architecture can be.

For dense mm-wave networks, self-backhauling is a solution envisioned for backhaul

provisioning to the mm-wave APs. The integration of these two architectural enablers

is mainly about making the right decision on the split between the cloud and radio,

and about deploying the right type of TRPs that are handling either RF up to MAC, or

up to the PDCP, in case where self-backhauling performance is far from ideal. In case

of centralized deployment, the central node may be configured to support a multitude

of slice instances, with flexible configuration of the slice availability in the distributed

nodes.

Self-backhauling is an enabler for multi-connectivity since connection between base

stations over Xn interface is needed. Multi-connectivity needs to be integrated with

self-backhauling which will enable fast data forwarding for buffer synchronization

between the APs involved (in case where service flow is split on the PDCP level). Self-

backhauling should be transparent to the UE, when network slicing is used in a

heterogeneous network. However, at the network level the RRM could turn to be

complex, especially when the spectrum will be shared between multiple slices but also

between self-backhauling and access.

The new mobility state RRC_INACTIVE requires integration with several other

enablers. The RRC-INACTIVE state requires measurements and other information

from UE for its proper configuration. In case of inter-RAT multi-connectivity, available

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measurements might vary and integration requires taking proper measurements and

processing them, in order to have information that can be used to change mobility

states and configure RRC_INACTIVE state to achieve gains from using this new

mobility state. In case of network slicing, it is expected that the slice availability will be

consistent at least within the tracking areas, which a UE can be configured with and a

UE in inactive mode can freely reselect to other cells within the configured tracking

area index list (TAI-list) and resume its connection in its previous slice. If a UE in

RRC_INACTIVE selects a cell outside the configured TAI-list, it will resume its

connection and perform a tracking area update, whereupon the CN can redirect it to

the proper slice, if needed. When the UE resumes the connection, the UE may need to

consider slice-specific access control policies broadcasted by the network.

When considering operation of mm-wave clusters under presence of RRC_INACTIVE

state, the impact on cluster reconfiguration, cluster updates and buffer synchronization

needs to be considered.

Self-backhauling needs to be aware of RRC_INACTIVE and APs need to keep S1

connection to the core under mobility of the UE in the new state.

In Section 3.1, we described a framework that helps to combine various architectural

solutions, via introduction of additional abstraction layers.

6 Conclusions

In this paper we have described the challenges and viewpoints identified by

mmMAGIC project related to the successful deployment of mm-wave networks.

Focusing on a generic RAN architecture (still under study within 3GPP Working

Groups), both for standalone and non-standalone deployments, a multi-RAT multi-

layer management framework is first proposed based on so-called Green Link Budget

metric. Five architectural enablers are then described which can be a key for successful

deployment of mm-wave networks, namely: multi-connectivity, a new mobility state –

the RRC_INACTIVE, mm-wave cell clustering, network slicing and self-backhauling.

Network slicing is briefly introduced as the basic glue where multiple services and

business operations are realized independently on a shared infrastructure. Some

technical enablers are then presented with technical detail, that are considered to bring

significant benefits to mm-wave system operation. Finally, interrelations between the

above mentioned technical enablers are also explained, to round up the different

elements into a holistic concept for mm-waves.

To conclude the paper, we highlighted the identified architectural enablers envisioned

for 3GPP LTE Rel-13. The multi-connectivity concept extends dual connectivity in

terms of number of base stations that can be involved for connection (in dual

connectivity two, and for multi-connectivity, two or more APs).

Since mm-wave systems should effectively operate in standalone deployments, the

modification in the protocol stack is needed. To handle infrequent transmissions of

small packets (e.g. traffic generated by smartphone applications working in the

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background) the new RRC_INACTIVE state needs to be introduced to complement the

states standardized for those present in existing technologies.

The novelty in the architecture related to the mm-wave cell clustering is mainly due to

introduction of the new logical entity and named cluster head. The cluster of mm-wave

cells is different from the group of cells used in dual-connectivity (LTE) or multi-

connectivity (5G) and the cluster head has responsibilities beyond those of MeNB e.g.

coordinating the beams, managing buffers of APs in the cluster.

The mm-wave system will also support network slicing, where the same physical

infrastructure can be configured as multiple logical networks operated separately.

Self-backhauling does not exist in LTE Rel-13 – something that resembles it is LTE-Rel-

10 relaying but the self-backhauling strives for simplification and doesn’t have

overhead coming from backward compatibility. Relays were introduced for mitigating

coverage problems and self-backhauling can help both in extending capacity and

coverage. The self-backhauling is based on dynamic scheduling (different from LTE’s

semi static scheduling). The architecture for self-backhauling supports backhaul

mobility and backhaul multi-connectivity. LTE relaying was standardized for

distributed deployments whereas self-backhauling works both for centralized and

decentralized deployments with various split points.

All five key architectural enablers introduce novelty when compared to LTE Rel-13

architecture and enables operation that will satisfy requirements identified for the use

cases envisioned for mm-wave RAT.

7 Acknowledgement

The research leading to these results received funding from the European Commission

H2020 programme under grant agreement n°671650 (mmMAGIC project).

8 References

[3GPP TS 36.300] 3GPP TS 36.300 V13.2.0 E-UTRA, E-UTRAN, Overall

Description; Stage 2, 2015.

[3GPP TS.36.304] 3GPP TS.36.304, UE procedures in IDLE mode.

[3GPP TS.36.331] 3GPP TS.36.331, Radio Resource Control (RRC) specification.

[3GPP TR.38.801] 3GPP TR.38.801, Study on New Radio Access Technology: Radio

Access Architecture and Interfaces.

[3GPP TR.36.842] 3GPP TS.36.842, Study on Small Cell enhancements for E-UTRA

and E-UTRAN; Higher layer aspects.

[BDO+13] C. J. Bernardos, A. De Domenico, J. Ortin, P. Rost and D.

Wübben, "Challenges of Designing Jointly the Backhaul and

Radio Access Network in a Cloud-Based Mobile Network," 2013

Future Network & Mobile Summit, Lisboa, 2013, pp. 1-10.

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[E14] Ericsson, “The Real-Time Cloud White Paper”, February 2014,

see http://www.ericsson.com/res/docs/whitepapers/wp-sdn-and-

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