Cross Layer Design of Heterogeneous Virtual MIMO Radio Networks with Multi-Optimization

Wei Chen, Heh Miao, Liang Hong, Jim Savage, Husam Adas College of Engineering, Technology & Computer Science

Tennessee State University Nashville, TN 37209, USA

(wchen, hmiao, lhong)@tnstate.edu; jim.savage@nashville.gov; adas@comcast.net

Abstract – In virtual MIMO technology, distributed single-antenna radio systems cooperate on information transmission and reception as a multiple- antenna MIMO radio system. In this paper, a new virtual MIMO communication scheme and routing protocol are cross layered designed for a wireless sensor network (WSN) to jointly achieve reliability, energy efficiency and delay reduction. The proposed communication scheme minimizes the intra communication in virtual MIMO nodes. It saves energy and reduces latency simultaneously at transmission links even when the diameters of virtual nodes are large. Given a required reliability, the proposed routing protocol simultaneously optimizes energy and latency along the route. Virtual MIMO nodes/links are allowed to be heterogeneous in order to apply the visual MIMO technology to a general WSN. A virtual MIMO radio network can be formed for any underlying WSN. The network is reconfigurable with low cost. The performance evaluation shows that the proposed design can fully realize the potential of the virtual MIMO technology and largely improve network throughput, network lifetime, and reliability in a WSN.

Keywords – wireless sensor networks; MIMO radios; virtual MIMO technology; cross-layer design; reconfigurable routing

1. INTRODUCTION

A network of inexpensive wireless micro sensor devices can be used for real time applications such as environment monitoring and vehicle tracking. Since micro sensor devices are equipped with a small processor, single-antenna radio and limited battery power, high networking performance and low energy consumption have been very challenging issues. Multiple Input Multiple Output (MIMO) radio transceivers employ multiple digital adaptive transmission and reception antennas which can provide extremely high spectral efficiencies by simultaneously transmitting multiple data streams in the same channel. MIMO technology has been used in WSNs for raising data rates, improving data transmission quality or extending transmission range, and saving energy [1-5]. However, MIMO technology requires terminal devices equipped with multiple antennas, which is unrealistic in many cases when considering the size, power consumption and cost of the terminal devices in wireless sensor

networks. Therefore, virtual MIMO technology that enables distributed individual single-antenna nodes cooperating on information transmission and reception as a multiple antenna array must take place. In this paper, we consider multiple cooperative WSN nodes as a single virtual MIMO node, and the transmission link between two virtual MIMO nodes as a virtual MIMO link. In [2], S. Cui and others proposed a communication scheme for transmitting multiple source data between two virtual MIMO nodes. The scheme minimizes the energy consumption and transmission delay through variable data rates by adjusting constellation size (bits per signal). In the scheme, a large number of intra transmissions are required in the virtual MIMO nodes. The scheme needs less energy and latency than the traditional non–cooperative Single Input Single Output (SISO) approach, but only when the diameter of virtual MIMO nodes is very small, where the diameter is defined as the largest distance between any two WSN nodes inside a virtual MIMO node. In [6], S. Hussain and others proposed a communication scheme similar to that in [2]. In order to reduce the transmission energy, multiple source data are assumed to be aggregated to a single data, though the assumption may not be true in applications. In [7], instead of a MIMO transmission, a MISO (Multiple Input Single Output) transmission is proposed between two virtual MIMO nodes. Compared with the schemes in [2, 6], it needs fewer intra transmissions in virtual MIMO nodes. In [6-8], routing protocols are jointly designed with the communication schemes. In [6, 7], cooperative transmission and reception nodes are selected at each link along the route at every routing process, where [7] requires the same number of cooperative nodes in each virtual MIMO node while [6] allows the heterogeneity in virtual MIMO nodes/links. Both protocols are designed only for saving energy. In [7-8], the diameter of each virtual MIMO nodes, the size of each virtual MIMO node (the number of WSN nodes in the virtual MIMO node), and the length of each virtual MIMO link have to be same. It is very difficult to construct such a virtual MIMO network unless the underlying WSN is very dense or the sensor nodes are manually deployed. In the above research work, the evaluation includes a comparison only with the traditional non-cooperative approach. In this paper a new virtual MIMO communication scheme and routing protocol are cross layer designed for a general

978-1-4244-6534-7/10/$26.00 ©2010 IEEE

wireless sensor network to jointly achieve reliability, energy efficiency and delay reduction. The proposed communication scheme minimizes intra data communication in virtual MIMO nodes. It can simultaneously achieve energy savings and reduce transmission delay at a communication link between two virtual MIMO nodes even when the diameter of virtual MIMO nodes is large. Given a required reliability, energy and latency are simultaneously optimized along the route through multiple parameters of bandwidth, size and diameter of virtual MIMO nodes, and length of a virtual MIMO link by adjusting the constellation size. The routing protocol is reconfigurable with low cost by using MIMO invoked advantage on transmission range extension. In order to apply virtual MIMO technology to a general WSN, the virtual MIMO nodes/links are allowed to be heterogeneous: the number of WSN nodes in a virtual MIMO node, the diameter of a virtual MIMO node, and the length of a virtual MIMO link can be different. A virtual MIMO radio network can be formed by the proposed algorithm for any underlying WSN. The performance evaluation shows that the proposed design can fully realize the potential of the virtual MIMO technology and largely improve network throughput, QoS, and network lifetime. Our evaluation includes the comparison with the traditional non-cooperative approach and with other virtual MIMO cooperative approaches. 2. VIRTUAL MIMO RADIO NETWORK MODELING

Given a WSN, let V be the set of sensor nodes equipped with a single-antenna radio. A d-clustering of V is a node disjoint division of V, where the distance between two WSN nodes in the cluster is not larger than d. Let A and B be two d-clusters, and A’ and B’ be the subsets of A and B, respectively. Suppose there are mt nodes in A’ and mr nodes in B’. If the largest distance between a node of A’ and a node of B’ is not larger than D, a D-mt×mr virtual MIMO transmission link can be defined between A and B, where node i in A’ uses its antenna as the ith antenna cooperating the transmission and node j in B’ uses its antenna as the jth antenna cooperating the reception. According to mt = mr = 1, mt > 1 and mr = 1, mt = 1 and mr >1, mt > 1 and mr > 1, the virtual MIMO link is called SISO link, MISO link, SIMO link and MIMO link, respectively. Since mt nodes in A’ can form a MISO link with every node in B’, a Multi-MISO link consisting of mr multiple mt×1 MISO links can be formed between A’ and B’. Usually, d is much smaller than D. We assume that any two WSN nodes in a d-cluster are in the communication range with each other. A virtual MIMO radio network of the WSN can be represented as an undirected graph VMIMOG =

( VMIMOV , VMIMOE ), where VMIMOV is the set of the clusters,

and VMIMOE is the set of edges, where an edge (A,B)

VMIMOE∈ if VMIMOVA ∈ and VMIMOVB ∈ and there is a virtual MIMO link defined between A and B. There are many ways to define a virtual MIMO link between two clusters. We will discuss this in the following sections. In a virtual MIMO network, the size of a cluster, i.e., the number of

WSN nodes in the cluster, the diameter of a cluster, and the length of virtual MIMO links can be different. In the rest of the paper, the clusters are also called virtual MIMO nodes, and the nodes of the WSN in a virtual MIMO node are called primary nodes. In each virtual MIMO node there is a special primary node called the head node. The head node retains information of other primary nodes such as ID and battery power level, and the other primary nodes retain the information about the head. In a WSN, the information collected by one sensor or by multiple sensors needs to be transmitted to the sink. In Section 3, the data transmission at a virtual MIMO link will be discussed. In Section 4, the virtual MIMO network formation and routing protocol for relaying the information to the sink will be discussed.

3. COOPERATIVE COMMUNICATION SCHEMES

In this section, we first describe our MIMO communication scheme, then analyze and compare the scheme with Cui’s scheme [2] and Yuan’s scheme [7]. Suppose that there are mt primary nodes and mr primary nodes at the transmission side A and the reception side B, respectively. The proposed scheme is designed for sending k (mt ≥ k ≥ 1) multiple source information from the virtual MIMO node A to the sink. 3.1 PROPOSED MULTI-MISO SCHEME

Instead of a mt×mr MIMO link, a Multi-MISO link which consists of mr multiple mt×1 MISO links are formed between A and B. In a mt×mr MIMO link, the information received at each primary node in B must be sent to one place, say the head, for decoding which requires intra communication in B. However, in a Multi-MISO link the nodes in B do not cooperate with reception; therefore, the decoding can be done at each node in B without further intra communication. The cooperative transmission at each hop is described as follows: Transmission at First Hop (Figure 1 (a)) Step 1 (Local transmission at A): Each node i at A with source information iI broadcast its information to all other nodes using different timeslots. After

Figure 1 Cooperative Multi-MISO Scheme

B C

(b)Other hops

1st MISO link

A

(a) First hop

B

D

2nd MISO link

3rd MISO link

this step, each node in A has information sequence

1I 2I … kI . Step 2 (Transmission between A and B with mr multiple mt×1 MISO links): Each node i in A acts as the ith antenna encoding the sequence 1I 2I … `kI using the mt×1 MISO code system. All mt nodes in A broadcast encoded sequence to the mr nodes in B at the same time. Each of mr nodes in B receives mt encoded sequences, and then decodes them back to 1I 2I … kI using the mt×1 MISO code system. Transmission at Other Hops (Figure 1 (b)) In the other hops, only one step (Step 2 in the first hop) is needed. Suppose there are mt and mr cooperative nodes in transmission side B and in reception side C, respectively. Step 1 (Transmission between B and C with mr multiple mt×1 MISO links): Each node i in B acts as the ith antenna encoding the sequence 1I 2I … kI using the mt×1 MISO code system. All mt nodes in B broadcast the encoded sequence to the mr nodes in C at the same time. Each node of mr nodes in C receives mt encoded sequences, and decodes them back to 1I 2I … kI . In the proposed Multi-MISO scheme, there is no local transmission from the second hop. The information transmission from multiple nodes at the same time always contains a synchronization coordinated by the head. 3.2 OTHER COOPERATIVE COMMUNICATION SCHEMES

A. MIMO Scheme [2]

In the MIMO scheme, cooperative primary nodes in virtual node A and cooperative primary nodes in B form a single MIMO link (Figure 2).The information received at each node in B must be sent to the head node for decoding. Therefore, the scheme has one more step then the Multi-MISO Scheme for local communication at B. Transmission at First Hop Step 1: same as the Step 1 in the Multi-MISO Scheme. Step 2 (Transmission between A and B with a mt×mr virtual MIMO link): Each node i in A acts as the ith antenna encoding the sequence 1I 2I … kI using the MIMO code system. All mt nodes in A broadcast the encoded sequence to the mr nodes in B at the same time. Step 3 (Local transmission at B): Each node in B transmits the received sequences using different time slots to the head node. The head node decodes the received mr sequences back to 1I 2I … kI according to the MIMO code system. Transmission at Other Hops Step 1: the head node at the transmission side B broadcasts the sequence 1I 2I … kI to other local nodes. Step 2 and Step 3: same as those in the first hop.

B. MISO-Scheme [7]

In this scheme, cooperative nodes in virtual node A and the head node in B form a single mt×1 MISO link (Figure 3): Transmission at First Hop Step 1 (Local transmission at A): Each node i with source information transmits its information iI to the head using different timeslots. The head broadcasts received sequence

1I 2I … kI to the mt cooperative nodes ( mt cooperative nodes and the source nodes can overlap with each other). Step 2 (Transmission between A and B with a single mt×1 MISO link): Each cooperative node i acts as the ith antenna encoding the sequence 1I 2I … kI using the MISO code system. All mt nodes in A transmit the encoded sequence to the head node in B at the same time. The head in B decodes the received mt sequences back to 1I 2I … kI according to the MISO code system. Transmission at Other Hops Step 1: the head node at the transmission side B broadcasts the sequence 1I 2I … kI to other local nodes. Step 2: same as Step 2 in the first hop.

In the transmission at other hops, MISO Scheme needs

additional local communication compared with the proposed Multi-MISO Scheme.

3.3 EVALUATION OF COMMUNICATION SCHEMES

We assume that the MIMO systems in this paper are referring to the ones coded with Alamouti diversity code system using a flat Rayleigh fading channel. The path loss is modeled as a power falloff proportional to the distance squared. Given bandwidth B and constellation size b (bits per symbol), bB bits are transmitted per second. We consider a variable-rate system, where b is optimized at each MIMO link. In order to keep the model from being overly complicated, signal processing blocks (source coding, pulse-shaping, and

Figure 3 Cooperative MISO Scheme

First hop

d

A D

one 3×1MISO link

CBOther hop

one 3×1 MISO link

Figure 2 Cooperative MIMO scheme

First hop Other hops

A

D

one 4×2 MIMO link

CB

one 2×3 MIMO link d

digital modulation) are intentionally omitted. In a cooperative communication scheme, a head may need to broadcast signal bits for synchronization. We also assume that the time and energy for synchronization can be omitted. The methodology used here can be extended to use other MIMO coding systems which include the signal processing blocks and synchronization A. Formula

The following formulas are used to evaluate energy and latency and can be found in [2, 9]. For local transmission, a κ -th power path loss with AWGN is assumed. We use )(r

Le to denote the energy cost per bit for broadcasting information from one node to r nodes at local MIMO nodes. Since the long-haul distance D between two virtual MIMO nodes is usually much larger than the diameter d of the virtual nodes, we assume that the long-haul transmission distance is the same for each primary transmitting node in a virtual MIMO link. We use ),,,( rtmrmteMIMO to denote the energy cost per bit for a mt×mr MIMO link with t nodes participating the transmission and r reception nodes participating the reception. Therefore, energy cost per bit for a mt×mr MIMO link, r multiple mt×1 MISO links, a traditional non-cooperative link are ),,,,( mrmtmrmteMIMO ),,,1,( rmtmteMIMO and

)1,1,1,1(MIMOe , respectively.

.5,10,)12(35.0

)12(3

,10,50,5.62,24.48 where

/21))()((

)21(4ln)12(34)1( )1(

5.37

2

2)(

sTdBN

dGPPP

nTPbB

PPrPP

GbPb

Ne

trfb

b

dsyncrct

trsynsyncrsynct

db

bb

frL

μα

σα

==+

−=

×====

×++++

+×−−+=−

),,(G

D)(4r),()1(

),,,( )2(

2t

2

rtPNMG

m,b,mtpe

rtmrmte

cflr

b

MIMO

+×+=λ

πα

,5),/()2(),( dBiGGbBPrPtPrtPwhere rtsyncrctc =++=

.40dBM l =

In the formula, dp , B, d, D, b ,n are the bit error rate, bandwidth, diameter of virtual MIMO node, length of virtual MIMO link, constellation size, and information size at a source node, respectively, ),( rtPc is the total circuit energy

and syncrct ppp ,, are the circuit energy for transmission,

reception and synchronization, respectively, and ),,,( mrmtbpe d can be numerically calculated by the

formula in [2].

B. Energy and Latency Analysis

Assume that the symbol period is Bts /1= , and the size

of information is in bits at each source node i. We use indices i and j to denote nodes i and j at the cooperative transmission and reception sides, respectively. We use Lb , 0b ,

MIMOb , MISOb and MSIOMb − to denote the optimal constellation size b

at a local transmission in virtual MIMO nodes, a long haul traditional non-cooperative link, mt×mr MIMO link, single mt×1 MISO link, and r multiple mt×1 MISO links, respectively. They are calculated by minimizing ,Le

),1,1,1,1(MIMOe ),,,,( mrmtmrmteMIMO

),1,,1,( mtmteMIMO

and ),,,1,( rmtmteMIMO respectively. We assume that the

number of source information is the same as the number of primary nodes in the transmission side at the first hop. (1) Energy and Latency at the First Hop (i) Traditional SISO Non-Cooperative Scheme For the SISO long-haul transmission in the traditional non-cooperative approach, mt multiple source information are transmitted one after another from transmission side to reception side. The energy and latency are as follows:

∑=

=mt

i

MIMOiitra enE

1

)1,1,1,1( and ∑=

=mt

i i

istra b

ntT

10

(ii) MIMO Scheme According to [2], in the MIMO scheme, mr cooperative nodes at the receptions side quantize each symbol they receive into

rn bits, and then transmit all the bits to the head node. The energy and latency are as follows:

nn)1(

),,,()1(

1sr

11

∑

∑∑

=

==

+

+−=

mr

j

Lj

mt

ii

MIMOLi

mt

iiMIMO

e

nmrmtmrmtemtenE

)11(11 1∑∑ ∑

== =

++=mr

jsrL

j

mt

i

mt

iiMIMOL

i

isMIMO nn

bn

bbn

tT

where ∑=

=mt

iiMIMOs n

bn

1

1.

(iii) MISO Scheme

)1,,1,(

)1()1(

1

1i

1

∑

∑∑

=

==

+

−+=

mt

ii

MIMO

mt

ii

LLmt

iiMISO

nmtmte

nmteenE

)11(11 1i∑∑ ∑

== =

++=mt

ii

mt

iMISO

mt

iiLL

isMISO n

bn

bbn

tT

(iv) Proposed Multi-MISO scheme

),,1,()1(11∑∑

==− +−=

mt

ii

MIMOLi

mt

iiMISOM nmrmtmtemtenE

)1(11 i∑∑

==−− +=

mt

ii

mt

iMISOML

isMISOM n

bbn

tT

(2) Energy and Latency at Other Hops Suppose 1I 2I … kI is the information received at the reception side in the first link and its size is n. (i) Traditional SISO Scheme

neE MIMOtra )1,1,1,1(= , 0b

ntT s

tra =

(ii) MIMO Scheme

)11 1(

n )1(

),,,()1(

1

r1

∑

∑

=

=

++=

+

+−=

mr

isrL

jMIMOLsMIMO

s

mr

j

Lj

MIMOLMIMO

nnbbb

ntT

ne

nmrmtmrmtenmteE

(iii) MISO Scheme )1,,1,()1( nmtmtenmteE MIMOL

MISO +−=

)11( MISOLsMISO bbntT +=

(iv) Proposed Multi-MISO scheme ),,1,( nmrmtmteE MISOM

MISOM−

− =

MISOMs

MISOM bnt

T −− =

3.4 NUMERICAL RESULTS

In the evaluation, we set B = 10k/20k/30k, d = 1m–16m, D = 20m–150m, mt = 1–4, mr = 1–4, source information in =20k

bit, and .10 3−=dP (1) Performance at the first hop Figure 4 and Figure 5 figures show the performance when B = 20k, d = 2m and mt = mr = 2, and d = 10m and mt = mr =4. According to our results, when d, mt and mr get larger, the proposed Multi-MISO scheme needs less energy and/or latency than other schemes. (2) Performance at other hops Figure 6 shows the performance when B = 20k, d = 1m, mt = mr = 4, and n = 40k. According to our results, the Multi-MISO scheme takes less energy and less latency than the MIMO scheme and the MISO schemes in most cases; it takes less energy and less latency than the traditional scheme if D is larger than 30 m – 70 m when d changes from 1m – 16m.

The results show that the Multi-MISO scheme reduces latency and save energy better than other cooperative schemes in most of the time. The reason is that it has less

Figure 5 Energy consumption and latency in the first hop

when d = 10m and mt = mr = 4

Figure 4 Energy consumption and latency in the first hop when d = 2m and mt = mr = 2

intra/local communication. The results also show that the Multi-MISO scheme uses less energy than traditional SISO scheme though it needs additional local communications. The reason is that a Multi-MISO link (also a MIMO link or a MISO link) need less energy than a traditional SISO link (see formula in Section 3.3 A). In each scheme, constellation size b is determined optimally by minimizing the energy consumption. The optimal constellation size b in the Multi-MISO scheme is larger than that in the traditional scheme. This explains the reason why the Multi-MISO scheme also has less latency than the traditional scheme though the Multi-MISO scheme needs additional communications in the first hop.

4. RECONFIGURABLE ROUTING PROTOCOL

In this section, we discuss virtual MIMO network formation and reconfigurable routing protocol. We assume that the transmit range of WSN nodes can be selected by adjusting their transmission power. A virtual MIMO network is formed from a given WSN by clustering. Each cluster has a cluster head (CH) which can control and synchronize the cooperative transmission and reception. The CHs form a multi-hop routing backbone. The cooperative communication scheme proposed in Section 3 is incorporated into each hop in the transmission on the backbone. In some research works such as [7], the cooperative nodes are selected at each link along the route in each routing process. In our protocol, the clusters and the routing backbone are initialized only once.

They are reconfigurable with a very small topology change, and can be used for data transmission during the entire network lifetime. Therefore, the overhead of the time and energy for building and maintain clusters and the backbone tree are very limited. The algorithms in this section assume that Carrier Sense Multiple Access with Collision Avoidance (CSMA/CA) is the MAC used to avoid the communication collisions at the link layer. 4.1 FORMATION OF VIRTUAL MIMO NODES

Given a WSN, the following clustering algorithm divides the WSN nodes into node-disjoint clusters. To decide CHs, each node u declares a neighbor node v which has the smallest ID to be u’s CH. However, if there is any node who declares u as its head, u changes itself to be a CH. Algorithm 1 Formation of d-Clusters Input: a WSN of n nodes, and communication range d/2. Output: node-disjoint clusters, where in each cluster one node is CH and the others are cluster members (CMs), the head node knows member’s IDs and the members know the head’s ID. The distance between two nodes in the cluster is not larger than d. Each node u executes the following rounds: Round 1: u broadcasts its ID, and receives the IDs broadcasted from its neighbors. Round 2: (1) u selects a node v including itself which has the smallest ID in the IDs received from its neighbors, and (2) u sets v to be u’s CH. u transmits (u, v, “head-declare”) to v, and receives the head declare messages from its neighbors. Round 3: (1) If in the received messages, u finds at least one neighbor v who declares u as v’s CH, u sets itself as a CH; u adds v to its member-list for each received message (v, u,“declare-head”), (2) If u is a CH, u broadcasts head-confirmation message (u, “head-confirm”), and (3) u receives the head-confirmation messages from its neighbors. Round 4: If u receives a message (v, “head-confirm”) and v is in u’s member-list, u removes v from u’s mmber-list. When the clusters are formed, d is the transmission range for the intra communication in the clusters. 4.2 ROURTING BACKBONE

The routing backbone is a Spanning Tree of the CHs, where each CH represents a cluster or virtual MIMO node. The following algorithm is based on a distributed Breadth First Search algorithm. Algorithm 1 Formation of Routing Backbone Input: m CHs, a sink s, and initial transmission range D Output: A spanning tree of the m CHs and the sink, where the sink is the root, each CH knows its parent and its children in the backbone, the distance between two neighboring CHs in the backbone is not larger than D. Sink s executes the following rounds: Round 1: s broadcasts (s, “find children”), changes its status to “reception”, and receives the responses. Round 2: If s receives message (u, s, “child”), s adds each u

Figure 6 Energy consumption and latency in other hops when d = 10m, mt = mr = 4, and n = 40k

to its children list; Other nodes execute the following round repeatedly 2L/D times (L is the diameter of the underlying WSN) : (1) If u received messages (v, “find children”) and u’s status is not “reception”, (i) u selects a message (w, “find children”) from the received messages with the weakest signal that is larger than the threshold, and sets w to be u’s parent; (ii) u transmits (u, w, “child”) to w ; (iii) u sends (u, “find children”), and (iv) u changes its status to “reception”. (2) If u’s status is “reception” and u receives a messages (v, u, “child”), u adds v to u’s children list. In the above algorithm, D is the initial transmission range set for two neighboring CHs in the routing backbone. 4.3 NETWORK RECONFIGURATION

We suppose each CH maintains the following information after the backbone is formed: (1) CMs’ IDs in the cluster and their battery power levels, and (2) the transmission range to each neighboring CH in the routing backbone (it is initialized as D), and the size of the cluster that each neighboring CH represents. In the following algorithms, we suppose that whenever a CH updates its CMs or changes its neighbors (either the parent or children) in the routing backbone, it updates the above information at the same time.

A. Head-rotation and link-jumping

Functions head-rotation and link-jumping are designed to maximize the network lifetime. Head-rotation is designed to evenly use WSN nodes in a cluster. In the routing backbone, when a CH is running out of battery energy or moving out, Link-jumping is invoked to make u’s parent connect to u’s children by extending their transmission range so that the routing backbone can still be connected. Link-jumping is enabled by MIMO technology since, by using MIMO radio systems, transmission range can be largely extended without using to much extra energy. Algorithm 3 Head-Rotation (u: CH node, e: energy threshold, d: transmission range in clusters) 1. u checks its battery energy; 2. if u’s energy level is lower then e and there are no CMs whose energy level is larger than e, u invokes link-jumping operation; else u selects a CM v from its cluster which has the largest energy level; u broadcasts a head-rotation request “new head is v” using transmission distance d; when v receives the request and information from u, v changes its status to be CH, and deletes u from its member list; when any other members, w, of u receive the request from u, w changes v to be its CH. Algorithm 4 Link-Jumping (u: CH node) 1. u broadcasts a link-jumping request with the ID of u’s parent v and transmission range of u and v using transmission range max{d(u,x) | x is u’s backbone neighbor and d(u,x) is the transmission range of u and x}. 2. When any child, w, of u receives the Link-jumping request, w sets u’s parent v to be its parent, and sets the transmission distance from w and v to be d(w,v) = d(w,u)+d(u,v). In the link-jumping algorithm, in order to reach every

neighbor, u sends the request using the largest distance among u and its neighbors. Head-rotation and Link-jumping can be completed in one hop communication. B. Reconfiguration functions

We use node-joining and node-leaving operations for reconfiguring the virtual MIMO network. In the node-joining operation, we suppose that a new node new is a neighbor with at least one node of the backbone in transmission range D. If new can find a CH that is within distance d/2, new becomes a CM of this CH. Otherwise, new becomes the CH and the only node in a new cluster, and new sets one of the neighboring CHs within D transmission range to be its parent in the backbone tree. Algorithm 5 Node-Joining(new: node for joining) Repeat the following rounds until new finds a parent in the backbone tree 1. new broadcasts a request “I want to join” using

transmission range d/2; 2. If a CH node receives the request, v sets u to be its CM,

and sends a message containing its IDs and status back to new;

3. If new receives the message from a CH node v, it sets its status to be a CM and sets v to be its CH. Otherwise, (i) new broadcasts a request “I want to join” using transmission distance D, (ii) if a CH node receives the request, it transmits its ID back to new, (iii) new selects one, say w, from the received IDs and sets it to be new’s parent, and then transmits a message to w to declare that w is new’s parent, (iv) when w receives the message, w sets new to be its child in the routing backbone.

Node-leaving is a tough task in a cluster-based WSN [10] without using MIMO technology. However, by using Head-rotation and Link-jumping enabled by MIMO technology, the task can be finished in one hop communication. Assume that a node lev is running out of the battery or leaving the WSN. The following algorithm reconfigures the clusters and the routing backbone. Algorithm 6 Node-Leaving(lev: node for leaving) If lev is a CM, lev broadcasts a request “lev is leaving” using transmission distance d, and lev leaves (move out or turn off the power). When lev’s CH receives the request, it deletes lev from its member list. If lev is a CH, lev invokes head-rotating function (when the function finishes, either a CM will replace lev if there are other CMs in the cluster, or, if there is no any CMs in the cluster, lev’s children in the backbone will connect to lev’s parent in the backbone parent by invoking a Link-jumping operation) and lev leaves. 4.4 ROUTING ALGORITHMS

The routing algorithms for broadcast, data gathering, and unicast over the routing backbone are similar to those in [1]. In a broadcast, data from the sink is delivered to every node through the backbone using distributed DFS or BFS in a top down manner. In data gathering, data are gathered using the

routing backbone in a bottom up manner. In unicast, the route for data transmission between two nodes can be built by constructing a route via the root of the backbonet. We omit the details because of the space limitation.

4.5 SIMULATION AND EXPERIMENTAL RESULTS

In this section, energy savings and latency reduction are evaluated when multiple source data are relayed from a virtual MIMO node hop by hop to the sink in the virtual MIMO network. An underlying WSN network is formed by randomly deploying WSN nodes in a 400m×400m field. Virtual MIMO nodes and the routing backbone are formed by the algorithms in Section 4.1 and 4.2. The performance is investigated in various virtual MIMO networks by changing the average size k of virtual MIMO nodes from 2 to 4, the diameter d of virtual MIMO nodes from 2m to 10 m, and the transmission range D of virtual MIMO links from 50m to 150m. Performance is evaluated along the route. The number of cooperative WSN nodes at each virtual MIMO node is set to be the smaller one of 4 and the size of the virtual MIMO node. In the simulation, four source data with 20K bits each are relayed back to the sink. Due to space limitations, we only show the performance in Figure 7 for the case that d = 10m, k = 4, B = 20K, and 310−=bP when D changes from 50m to 150m. The results show that the proposed approach (Chen) uses less energy and produces lower latency compared with [2] (Cui), [7] (Yun) and traditional (tra) non-cooperative approaches.

ACKNOLOGYMENT This work was performed under contract with US AFRL/RY (2009-2010).

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Figure 7 Energy and Latency for relaying multiple source data in virtual MIMO networks