Elsevier

Computer Networks

Volume 55, Issue 8, 1 June 2011, Pages 1711-1718
Computer Networks

Rate adaptation with joint receive diversity and power control for cognitive radio networks

https://doi.org/10.1016/j.comnet.2011.01.001Get rights and content

Abstract

A joint receive diversity and power control (JRDPC) algorithm is proposed for cognitive radio networks. By this algorithm, the quality of service for the primary user can be ensured and the secondary user (SU) can make its signal-to-interference-plus-noise ratio (SINR) converge to the SINR requirement. To realize rate adaptation, we propose the rate adaptation algorithm that works with the proposed JRDPC algorithm. We assume that there is a throughput requirement (which is determined by the transmission rate and the SINR), and the proposed rate adaptation algorithm aims to adapt SUs transmission rate to the SINR so that SUs adapted transmission rate can meet the throughput requirement. Simulation results show that compared to rate adaptation without joint receive diversity and power control, the proposed rate adaptation algorithm increases SUs probability of feasibility (for making SUs adapted transmission rate meet the throughput requirement).

Introduction

The studies of cognitive radio (CR) have recently attracted much attention from researchers [1], [2]. In these studies, the user can be categorized into the primary user (PU) and the secondary user (SU). All PUs and SUs operate in the same frequency band, thus they will cause cochannel interference to each other. Since PUs have higher priority for transmissions, the transmission of the SU is not permitted to affect the quality of service (QoS) of each PU. Therefore, one objective of CR networks is to increase SUs transmission rate while ensuring the QoS of each PU.

Apparently, cochannel interference is inevitable in CR networks. Nevertheless, cochannel interference can cause the reduction of SUs signal-to-interference-plus-noise ratio (SINR), which in turn necessitates the reduction of SUs transmission rate. To increase SUs transmission rate, some techniques for suppressing cochannel interference, such as beamforming (diversity) and power allocation (power control), are needed. Diversity is realized by combining uncorrelated multi-path signals, while power control is realized by allocating different power levels to different users. Conventional diversity employs fixed power allocation, thus it can only achieve the locally maximal SINR for that power allocation. If power control can be employed, we can obtain the globally maximal SINR for all power allocations. Therefore, beamforming (diversity) and power allocation (power control) can be jointly operated to further improve the performance [3], [4], [5], [11], [12]. In [1], some algorithms that employ joint beamforming and power allocation for maximizing the sum-rate of SUs in CR networks were proposed.

Like [1], we employ joint receive diversity and power control to enhance SUs transmission rate. However, this paper is different from [1] in the problem, objective and algorithm. We assume that there is a throughput requirement (which is determined by the transmission rate and the SINR) and consider the problem about adapting SUs transmission rate to the SINR. The objective in this paper is to make SUs adapted transmission rate meet the throughput requirement. Note that the Shannon formula is not used in this paper. The reason is that the channel capacity of the Shannon formula means the upper bound of the information, which is hard to attain via current communication techniques, therefore, we consider in this paper the throughput, which can be attained via modulation, channel coding and ARQ. In addition, we use in this paper the iterative algorithm instead of the optimization based approach used in [1] to determine the diversity weight and the power level.

In [12], we proposed the distributed joint diversity and power control with ratioed power (DJDPC-RP) algorithm, in which the powers of the users connected to the same base station are ratioed to each other, for cellular networks. In this paper, we propose a joint receive diversity and power control (JRDPC) algorithm for CR networks. In this algorithm, the powers of the users connected to the same base station are not ratioed to each other and the initial power assignment ensures the QoS of the PU. We show that the QoS of the PU will be ensured during (and after) the execution of the JRDPC algorithm and the JRDPC algorithm can make SUs SINR converge to the SINR requirement.

In wireless networks, the transmission rate needs to be adapted to the wireless environments (such as the channel state and the interference condition), and power control can be incorporated into rate adaptation to enhance the transmission rate. Therefore, rate adaptation with power control has been an important research topic in wireless communications [8], [9]. To realize rate adaptation with joint receiver diversity and power control, we propose in this paper the rate adaptation algorithm that works with the proposed JRDPC algorithm for CR networks. In our study, we assume that each SU has its throughput requirement, and the rate adaptation algorithm aims to make the adapted transmission rate meet the throughput requirement for all SUs. Note that in real applications, owing to the channel condition and the interference, the throughput requirement is not guaranteed to be attained. Therefore, we consider the best-effort service, which does its best to adapt the transmission rate so that the adapted transmission rate can meet the throughput requirement.

The rest of this paper is organized as follows. Section 2 describes the investigated system model. The JRDPC algorithm is proposed in Section 3, and the JRDPC based rate adaptation algorithms are proposed in Section 4. Numerical results are discussed in Section 5. Finally, we draw some conclusions in Section 6.

Section snippets

System model

We consider the PU network and CR network studied in [1], and we adopt the single input multiple output (SIMO) model used in [1]. The considered PU network and CR network consist of N PUs and K SUs, respectively. We assume that all SUs are connected to the same base station (BS) that has M receive antennas, also, we assume that all PUs and SUs operate in the same frequency band. The received signals at the receive antenna array of the BS is represented by the following model:x=Hz+H^zˆ+n,where x

Joint receive diversity and power control

In this section, we propose the joint receive diversity and power control (JRDPC) algorithm, which is executed for several iterations, for CR networks. Let pim be the transmit power of SUi in the mth iteration of the JRDPC algorithm and let pi0=αP¯i, where 0 < α  1 (for satisfying (3)). Consequently, to satisfy (2), we must havei=1i=KαP¯ign,iTnforn=1,2,,N.As will be shown later, we have to maximize α so that the JRDPC algorithm can achieve the SINR requirement of SUi, thus we should find the

Rate adaptation with JRDPC

The SINR discussed in the last section can be associated with the rate adaptation. In fact, the SINR can be expressed asSINR=(Eb/I0)·(R/W),where Eb represents the bit energy, I0 represents the spectral density for the interference and noise, R represents the transmission rate and W represents the bandwidth. In practice, the signal quality is often characterized by Eb/I0 (bit-energy-to-interference-density ratio) because, given a transmission technology, the bit error rate can be derived from Eb/

Numerical results

In this section, we present the simulation results obtained by simulating the CR network. The link gain (and power gain) between transmitter l and receiver i is inversely proportional to SliDliα, where Sli is the shadowing factor (which models power variation due to shadowing) between transmitter l and receiver i, Dli is the distance between transmitter l and receiver i, and α is a constant that models the large scale propagation loss. All shadowing factors Sli are assumed to be independent,

Conclusion

We proposed in this paper the JRDPC algorithm, by which the QoS of the PU can be ensured and the SU can make its SINR converge to the SINR requirement, for CR networks. We further proposed in this paper the RA-JRDPC algorithm, which works with the JRDPC algorithm, for rate adaptation in CR in networks. The RA-JRDPC algorithm adapts SUs transmission rate to the SINR so that SUs adapted transmission rate can achieve the required transmission rate. Simulation results show that compared to rate

Acknowledgments

The author thanks the anonymous reviewers for their valuable comments which improved the presentation of the paper.

Jui Teng Wang received the B.S., M.S. and Ph.D. degrees from National Chiao Tung University, Hsinchu, Taiwan, all in communication engineering. He is now a professor with the Graduate Institute of Communication Engineering, National Chi Nan University, Puli, Nantou, Taiwan. His research interests are in wireless communications, wireless networks and software radio.

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    One example of the above scheme is the scheme proposed in [3], which uses joint beamforming and power allocation to increase SUs' transmission rate while ensuring the QoS of each PU. Previous studies of power control for CR (such as those in [3,8,9]), though have different characteristics and objectives (such as beamforming in [3], rate adaptation in [8] and channel allocation in [9]), use the fixed base station assignment for power control. To effectively take advantage of the concept of CR, we manage to execute power control for CR with the variable base station assignment, which realizes the base station sharing in addition to the spectrum sharing.

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Jui Teng Wang received the B.S., M.S. and Ph.D. degrees from National Chiao Tung University, Hsinchu, Taiwan, all in communication engineering. He is now a professor with the Graduate Institute of Communication Engineering, National Chi Nan University, Puli, Nantou, Taiwan. His research interests are in wireless communications, wireless networks and software radio.

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