Rate and power allocation in fading multiple access channels

We consider the problem of rate and power allocation in a fading multiple-access channel. Our objective is to obtain rate and power allocation policies that maximize a utility function defined over average transmission rates. In contrast with the literature, which focuses on the linear case, we present results for general concave utility functions. We consider two cases. In the first case, we assume that power control is possible and channel statistics are known. In this case, we show that the optimal policies can be obtained greedily by maximizing a linear utility function at each channel state. In the second case, we assume that power control is not possible and channel statistics are not available. In this case, we define a greedy rate allocation policy and provide upper bounds on the performance difference between the optimal and the greedy policy. Our bounds highlight the dependence of the performance difference on the channel variations and the structure of the utility function.

[1]  Xin Wang,et al.  Energy-Efficient Resource Allocation in Time Division Multiple-Access over Fading Channels , 2005, ArXiv.

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

[3]  John M. Cioffi,et al.  SPC10-2: Iterative Water-filling for Optimal Resource Allocation in OFDM Multiple-Access and Broadcast Channels , 2006, IEEE Globecom 2006.

[4]  Derong Liu The Mathematics of Internet Congestion Control , 2005, IEEE Transactions on Automatic Control.

[5]  Michael L. Honig,et al.  Resource allocation for multiple classes of DS-CDMA traffic , 2000, IEEE Trans. Veh. Technol..

[6]  Shlomo Shamai,et al.  Information-theoretic considerations for symmetric, cellular, multiple-access fading channels - Part I , 1997, IEEE Trans. Inf. Theory.

[7]  John M. Cioffi,et al.  Scheduling for Fading Multiple Access Channels with Heterogeneous QoS Constraints , 2007, 2007 IEEE International Symposium on Information Theory.

[8]  S. Shenker Fundamental Design Issues for the Future Internet , 1995 .

[9]  Sriram Vishwanath,et al.  Optimum power and rate allocation strategies for multiple access fading channels , 2001, IEEE VTS 53rd Vehicular Technology Conference, Spring 2001. Proceedings (Cat. No.01CH37202).

[10]  David Tse,et al.  Multiaccess Fading Channels-Part I: Polymatroid Structure, Optimal Resource Allocation and Throughput Capacities , 1998, IEEE Trans. Inf. Theory.

[11]  Shlomo Shamai,et al.  Information-theoretic considerations for symmetric, cellular, multiple-access fading channels - Part II , 1997, IEEE Trans. Inf. Theory.

[12]  K. Schittkowski,et al.  NONLINEAR PROGRAMMING , 2022 .

[13]  Asuman E. Ozdaglar,et al.  Resource Allocation in Multiple Access Channels , 2007, 2007 Conference Record of the Forty-First Asilomar Conference on Signals, Systems and Computers.

[14]  Seong-Jun Oh,et al.  Optimal resource allocation in multiservice CDMA networks , 2003, IEEE Trans. Wirel. Commun..

[15]  Xin Wang,et al.  Power-Efficient Resource Allocation for Time-Division Multiple Access Over Fading Channels , 2008, IEEE Transactions on Information Theory.