Power and Resource Allocation for Orthogonal Multiple Access Relay Systems

We study the problem of joint power and channel resource allocation for orthogonal multiple access relay (MAR) systems in order to maximize the achievable rate region. Four relaying strategies are considered; namely, regenerative decode-and-forward (RDF), nonregenerative decode-and-forward (NDF), amplify-and-forward (AF), and compress-and-forward (CF). For RDF and NDF we show that the problem can be formulated as a quasiconvex problem, while for AF and CF we show that the problem can be made quasiconvex if the signal-to-noise ratios of the direct channels are at least -3dB. Therefore, efficient algorithms can be used to obtain the jointly optimal power and channel resource allocation. Furthermore, we show that the convex subproblems in those algorithms admit a closed-form solution. Our numerical results show that the joint allocation of power and the channel resource achieves significantly larger achievable rate regions than those achieved by power allocation alone with fixed channel resource allocation. We also demonstrate that assigning different relaying strategies to different users together with the joint allocation of power and the channel resources can further enlarge the achievable rate region.

[1]  Hesham El Gamal,et al.  The three-node wireless network: achievable rates and Cooperation strategies , 2005, IEEE Transactions on Information Theory.

[2]  Aaron D. Wyner,et al.  The rate-distortion function for source coding with side information at the decoder , 1976, IEEE Trans. Inf. Theory.

[3]  Elza Erkip,et al.  User cooperation diversity. Part I. System description , 2003, IEEE Trans. Commun..

[4]  K. J. Ray Liu,et al.  Outage analysis and optimal power allocation for multinode relay networks , 2007, IEEE Signal Processing Letters.

[5]  Gregory W. Wornell,et al.  Cooperative diversity in wireless networks: Efficient protocols and outage behavior , 2004, IEEE Transactions on Information Theory.

[6]  Gerhard Kramer,et al.  Capacity Theorems for the Multiple-Access Relay Channel , 2004 .

[7]  Stephen P. Boyd,et al.  Convex Optimization , 2004, Algorithms and Theory of Computation Handbook.

[8]  Yingbin Liang,et al.  Gaussian orthogonal relay channels: optimal resource allocation and capacity , 2005, IEEE Transactions on Information Theory.

[9]  Michael Gastpar,et al.  Cooperative strategies and capacity theorems for relay networks , 2005, IEEE Transactions on Information Theory.

[10]  Gerhard Kramer,et al.  Cooperation vs. hierarchy: an information-theoretic comparison , 2005, Proceedings. International Symposium on Information Theory, 2005. ISIT 2005..

[11]  Abbas El Gamal,et al.  Capacity theorems for the relay channel , 1979, IEEE Trans. Inf. Theory.

[12]  Gerhard Kramer,et al.  Hierarchical sensor networks: capacity bounds and cooperative strategies using the multiple-access relay channel model , 2004, 2004 First Annual IEEE Communications Society Conference on Sensor and Ad Hoc Communications and Networks, 2004. IEEE SECON 2004..

[13]  Wei Yu,et al.  Joint optimization of relay strategies and resource allocations in cooperative cellular networks , 2006, IEEE Journal on Selected Areas in Communications.

[14]  Thomas M. Cover,et al.  Elements of Information Theory , 2005 .

[15]  Aylin Yener,et al.  Relay assisted F/TDMA ad hoc networks: node classification, power allocation and relaying strategies , 2007, IEEE Transactions on Communications.

[16]  Elza Erkip,et al.  User cooperation diversity. Part II. Implementation aspects and performance analysis , 2003, IEEE Trans. Commun..

[17]  Zhi-Quan Luo,et al.  An Efficient Algorithm for Optimum Power Allocation in a Decode-And-Forward Cooperative System with Orthogonal Transmissions , 2006, 2006 IEEE International Conference on Acoustics Speech and Signal Processing Proceedings.

[18]  A.J. van Wijngaarden,et al.  On the white Gaussian multiple-access relay channel , 2000, 2000 IEEE International Symposium on Information Theory (Cat. No.00CH37060).