International Conference on Computer and Communication Engineering (ICCCE 2012), 3-5 July 2012, Kuala Lumpur, Malaysia

978-1-4673-0479-5/12/$31.00 ©2012 IEEE

On QoS Routing in Mobile WiMAX Cognitive Radio Networks

Saeid Ghahremani Faculty of Information Science

and Technology University of Malaya

Kuala Lumpur, malaysia maziyarex@siswa.um.edu.my

Rashid Hafeez Khokhar Faculty of Information Scinece

and Technology University of Malaya

Kuala Lumpur, Malaysia rashid@um.edu.my

Rafidah Md Noor Faculty of Information Science

and Technology University of Malaya

Kuala Lumpur, Malaysia ketua_fsktmstk@um.edu.my

Ahmad Naebi Department of Electronic and Computer

Islamic Azad University, Qazvin Branch Qazvin, Iran

Ahmad.Naebi@gmail.com

Jahangir Kheyrihassankandi Faculty of Computing and Informatics

Multimedia University Selangor, Malaysia

Jahangir.Kheyrihas09@mmu.edu.my

Abstract—Throughput maximization is one of the main challenges in cognitive radio ad hoc networks, where the availability of local spectrum resources may change from time to time and hop by hop. Technologies based on 802.16e which called Mobile WiMAX (Worldwide Interoperability Microwave Access) promises to deliver high data rates over large distances and deliver multimedia services and are expected to play a major role in high speed broadband delivery. The maximum allowed number of hops must be carefully considered because higher number of hops will increase the transmission time and degrades the throughput and end to end delay. Multi-hop based network may also improve the system performance by using cooperative relay technique. There are various challenges for the routing in WiMAX mesh such as delay, long transmission scheduling, and increasingly stringent Quality of Service (QoS) support and load balance and fairness limitations. In this paper we use cognitive radio network composed of wireless devices able to opportunistically access the shred radio resource. The core of such networking paradigm is the capability of cognitive radio to monitor spectrum occupation to exploit spectrums holes for transition. Extensive simulations are conducted under MATLAB and compare the performance of our routing protocol with AODV for Mobile WiMAX environment. The propose algorithm shows high throughput, reduce end to end delay, and increase packet delivery ratio.

Keywords-Mobile WiMAX; AODV; Cognitive Radio Network (CRN)

I. INTRODUCTION The usage of radio spectrum resources and the regulation of

radio emissions are coordinated by national regulatory bodies like the Federal Communications Commission (FCC).The FCC assigns spectrum to licensed holders, also known as primary

users, on a long-term basis for large geographical regions. However, a large portion of the assigned spectrum remains under utilized as illustrated in Fig. 1.where users who have no spectrum licenses, also known as secondary users, are allowed to use the temporarily unused licensed spectrum.

IEEE 802.22 is the first standard for cognitive radio networks, in which, however, network entry and initialization, as well as the hidden incumbent problem have not yet completely been addressed. On the other hand, mobility is also an unexplored issue in cognitive radio networks.

Next generation communication networks, also known as dynamic spectrum access (DSA) networks, to utilize the spectrum more efficiently in an opportunistic fashion without interfering with the primary users. It is defined as a radio that can change its transmitter parameters according to the interactions with the environment in which it operates.

Figure 1. Spectrum usage.

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As primary users have priority in using the spectrum, when secondary users coexist with primary users, they have to perform real-time wideband monitoring of the licensed spectrum to be used. When secondary users are allowed to transmit data simultaneously with a primary user, interference temperature limit should not be violated [1]. If secondary users are only allowed to transmit when the primary users are not using the spectrum, they need to be aware of the primary users’ reappearance through various detection techniques, such as energy detection, feature detection, matched filtering and coherent detection.

II. RELATED WORK Several testbeds have been introduced for CR

technologies.BEE2 [4] provided a general and multi-purpose emulation platform to enable experimentation on use of spectra without interference. Its main purpose was to evaluate multiple-sensing algorithms on CR devices. Other platforms, such as ORBIT [5], provide open-access experimental environments to evaluate protocols and the efficiency of applications in real-world settings utilizing radio-grid emulators that consist of radio nodes such as 802.11 a/b/g and CR devices. It has, however, been difficult to support a considerably large number of nodes, including emerging radios, wired networks, and new protocol stacks, because the testbed has been intended for ad-hoc and mesh networks. The maximum number of nodes, moreover, is restricted to the actual number of radio devices. We recently introduced an adaptive wireless-network testbed [6] on MIRAI Simulation Framework (MIRAI-SF) [7] that was developed for heterogeneous wireless networks to resolve these issues.

The testbed provided scalability for more than ten thousand nodes by using real devices and virtual nodes; it also attained flexibility to enable any protocol or application to be configured. It could verify all the protocol levels, especially those in the Medium Access Control (MAC) layer and CR protocols, including the execution of applications, taking advantage of the capabilities of large-scale-network implementation. Worldwide Interoperability for Microwave Access (WiMAX) is a technology that bridges the gap between fixed and mobile access and offer the same subscriber experience for fixed and mobile user. The earliest version of WiMAX is based on IEEE 802.16 and is optimized for fixed and nomadic access, which is further extended to support portability and mobility based on IEEE 802.16e, also known as Mobile WiMAX.

In rural areas and developing countries, providers are unwilling to install the necessary equipment (optical fiber or copper-wire or other infrastructures) for broadband services expecting low profit.Broadband Wireless Access (BWA) has emerged as a promising solution for “last mile” access technology to provide high speed connections. IEEE 802.16 standard for BWA and its associated industry consortium, Worldwide Interoperability for Microwave Access (WiMAX) forum promise to offer high data rate over large areas to a large number of users where broadband is unavailable. This is the first industry wide standard that can be used for fixed wireless access with substantially higher

bandwidth than most cellular networks [8], [9]. Development of this standard facilitates low cost equipment, ensure interoperability, and reduce investment risk for operators. In the recent years, IEEE 802.16 working group has developed a number of standards for WiMAX. The first standard IEEE 802.16 was published in 2001 and focused on the frequency range between 10 and 66 GHz and required line-of-sight (LOS) propagation between the sender and the receiver [10].

A number of wireless routing protocols are already designed to provide communication in wireless environment, such as AODV, OLSR, DSDV, ZRP, LAR, LANMAR, STAR, DYMO etc. Performance comparison among some set of routing protocols are already performed by the researchers such as among PAODV, AODV, CBRP, DSR, and DSDV [11], among DSDV, DSR, AODV, and TORA [12], among SPF, EXBF, DSDV, TORA, DSR, and AODV [13], among DSR and AODV [14], among STAR, AODV and DSR [15], among AMRoute, ODMRP, AMRIS and CAMP [16], among DSR, CBT and AODV [17], among DSDV, OLSR and AODV [13] and many more. These performance comparisons are carried out for ad-hoc networks but none for Mobile WiMAX. For this reason, evaluating the performance of wireless routing protocols in Mobile WiMAX environment is still an active research area and in this paper we study and compare the performance of AODV, DSR, OLSR and ZRP routing protocols.

A. Cognitive Radio Functions A typical duty cycle of CR, as illustrated in Fig. 2, includes

detecting spectrum white space, selecting the best frequency bands, coordinating spectrum access with other users and vacating the frequency when a primary user appears. Such a cognitive cycle is supported by the following functions:

• Spectrum sensing and analysis.

• Spectrum management and handoff.

• Spectrum allocation and sharing.

Figure 2. Cognitive cycle.

Through spectrum sensing and analysis, CR can detect the spectrum white space (see Fig. 3), i.e., a portion of frequency band that is not being used by the primary users, and utilize the

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spectrum. On the other hand, when primary users start using the licensed spectrum again, CR can detect their activity through sensing, so that no harmful interference is generated due to secondary users’ transmission.

Figure 3. Illustration of spectrum white space.

In dynamic spectrum access, a secondary user may share the spectrum resources with primary users, other secondary users, or both. Hence, a good spectrum allocation and sharing mechanism is critical to achieve high spectrum efficiency. Since primary users own the spectrum rights, when secondary users co-exist in a licensed band with primary users, the interference level due to secondary spectrum usage should be limited by a certain threshold.

Network Architecture and Applications With the development of CR technologies, secondary users who are not authorized with spectrum usage rights can utilize the temporally unused licensed bands owned by the primary users. Therefore, in a CR network architecture, the components include both a secondary network and a primary network, as shown in Fig. 4.

A secondary network refers to a network composed of a set of secondary users with/without a secondary base station. Secondary users can only access the licensed spectrum when it is not occupied by a primary user. The opportunistic spectrum access of secondary users is usually coordinated by a secondary base station, which is a fixed infrastructure component serving as a hub of the secondary network. Both secondary users and secondary base stations are equipped with CR functions. If several secondary networks share one common spectrum band, their spectrum usage may be coordinated by a central network entity, called spectrum broker [3]. The spectrum broker collects operation information from each secondary network, and allocates the network resources to achieve efficient and fair spectrum sharing.

A primary network is composed of a set of primary users and one or more primary base stations. Primary users are authorized to use certain licensed spectrum bands under the coordination of primary base stations. Their transmission should not be interfered by secondary networks. Primary users and primary base stations are in general not equipped with CR functions. Therefore, if a secondary network shares a licensed spectrum bandwidth a primary network, besides detecting the spectrum white space and utilizing the best spectrum band, the secondary network is required to immediately detect the presence of a primary user and direct the secondary

transmission to another available band so as to avoid interfering with primary transmission.

Because CRs are able to sense, detect, and monitor the surrounding RF environment such as interference and access availability, and reconfigure their own operating characteristics to best match outside situations, cognitive communications can increase spectrum efficiency and support higher bandwidth service. Moreover, the capability of real-time autonomous decisions for efficient spectrum sharing also reduces the burdens of centralized spectrum management. As a result, CRs can be employed in many applications.

Figure 4. Network architecture of dynamic spectrum sharing.

III. PROPOSED ALGORITHM Spectrum/channel assignment is a well-studied problem in

traditional wireless networks. [18] Provides a comprehensive survey in the area of dynamic, fix, and hybrid allocation strategy, and compares their complexity, performance and the trade-offs.

However in CRN, compared to the traditional wireless networks, the fundamental difference is that the available spectrum bands/channels are dynamic and their availability changes all the time, which makes the traditional spectrum/channel assignment protocols do not work. Because of this fundamental difference, new protocols/standards are proposed, such as the ones in [19][20] and the well-known IEEE 802.22[21]. Available spectrum bands and can be aggregated into one channel.

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Figure 5. Spectrum aggregation using DOFDM. DOFDM carriers are on two.

On this study we try to send data on several spectrum in parallel mod in a moment, in the first pocket of data, receiver will catch information about other spectrums that sender have possibility to make connection, sender by checking its possibility will accept and transfer process will start on several predefined spectrum by transceiver controllers. In case of any loosing spectrum by primary users data of might transfer by other connected spectrums. An example of allocating spectrums for determined transited is shown in fig.6.

Figure 6. Example of spectrum allocating in parallel allocating patterns.

For high level understanding, [22] provides a survey. In [20], a Dynamic Open Spectrum Sharing (DOSS) MAC protocol is proposed: when assigning spectrums for a transmission between two users, they first negotiate on a pre-known control channel to tell each other their own available spectrum bands. In their common available bands, they choose the largest contiguous band, on which they start transmitting. During transmitting, if the transmission band turns unavailable, they suspend current data transmission and re-assign the spectrum. After a new spectrum band is assigned, the data transmission is resumed on the new band. So although the available spectrum bands are dynamic and their availability changes all the time in CRN, DOSS still works.

However the above works are based on contiguous channel assignment algorithms. In current contiguous channel assignment algorithms, each channel consists of only one contiguous spectrum fragment, so they cannot utilize small spectrum fragments whose bandwidths are smaller than the users’ demand.

IV. SIMULATION OPNET (from network simulator) is heavily used in ad-hoc

networking research, and support popular network protocols, offering simulation results for wired and wireless networks alike.

In our simulation, we consider a network of 50 nodes (one source and one destination) that are placed randomly within a

10000m X 10000m area and operating over 500 seconds. Multiple runs with different seed numbers are conducted and collected data is averaged over those runs.

The node movements (except base station) in these experiments are modeled using the random waypoint mobility model [24] with mobility speed ranging from 10 km/h to 100 km/h. We choose this range because WiMAX support medium mobility unlike cellular system.

A. Simulation Results Figure 7 shows the packet delivery ratio of AODV, CRN as

a function of mobility speed. These two protocols have packet delivery ratio of 100% when the nodes are stationary. However, packet delivery ratio decline when nodes begin to move. When looking at the packet delivery ratio (Figure 7) it can easily be observed that CRN perform much better than AODV.

Figure 7. Packet Delivery Ratio.

Figure 8 shows the average end-to-end delay from the source to the destination’s application layer. CRN demonstrates less delay than the other protocol due to their using different spectrum. It regularly updates its routing table. In case of AODV, which is reactive in nature, have higher delay. Among these different spectrum protocols, CRN demonstrates better performance.

Figure 8. Average End-to-End Delay.

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Figure 9, CRN demonstrates better performance in node mobility. CRN shows better performance in higher mobility than the other protocol.

Figure 9. Throughput.

V. CONCLUSION A performance comparison of two different Mobile

WiMAX routing protocols (AODV and CRN) is performed here using different mobility scenarios. Simulation has been conducted in Mobile WiMAX environment. From the result of our studies, it can be said that, on an average CRN perform better than AODV. It has less average end to end delay. However, for other metrics (packet delivery ration and throughput), AODV demonstrate poor performance.

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