Joint transmitter adaptation and power control for cognitive radio networks with target SIR requirements

Abstract In this paper we study joint transmitter adaptation and power control in the uplink of Cognitive Radio (CR) networks with target values imposed on the signal-to-interference +noise-ratios (SINR) at the CR receiver. We use a framework based on block transmissions and linear precoders to formulate this as a constrained optimization problem for which we discuss the conditions that must be satisfied by the optimal solution. We also present an algorithm which adapts the transmit precoder and power values incrementally until a fixed point is reached where the specified target SINRs are achieved with minimum transmitted power. Convergence of the proposed algorithm is discussed and is illustrated with numerical examples obtained from simulations.

[1]  Ekram Hossain,et al.  Resource allocation for spectrum underlay in cognitive radio networks , 2008, IEEE Transactions on Wireless Communications.

[2]  Joseph B. Evans,et al.  COGNITIVE RADIOS FOR DYNAMIC SPECTRUM ACCESS , 2007 .

[3]  R. Sundaram A First Course in Optimization Theory: Bibliography , 1996 .

[4]  Kyoung-Jae Lee,et al.  MMSE Based Block Diagonalization for Cognitive Radio MIMO Broadcast Channels , 2011, IEEE Transactions on Wireless Communications.

[5]  D. Popescu,et al.  Fading Channels and Interference Avoidance , 2004 .

[6]  Yuan Wu,et al.  Sensing Based Joint Rate and Power Allocations for Cognitive Radio Systems , 2012, IEEE Wireless Communications Letters.

[7]  Octavia A. Dobre,et al.  User admissibility in uplink wireless systems with multipath and target SINR requirements , 2010, IEEE Communications Letters.

[8]  R. Sundaram A First Course in Optimization Theory , 1996 .

[9]  Vijay K. Bhargava,et al.  Linear Precoding for Orthogonal Space-Time Block Coded MIMO-OFDM Cognitive Radio , 2011, IEEE Trans. Commun..

[10]  Sergio Barbarossa,et al.  Optimal Linear Precoding Strategies for Wideband Noncooperative Systems Based on Game Theory—Part I: Nash Equilibria , 2007, IEEE Transactions on Signal Processing.

[11]  Sergio Barbarossa,et al.  Optimal Linear Precoding Strategies for Wideband Non-Cooperative Systems Based on Game Theory—Part II: Algorithms , 2007, IEEE Transactions on Signal Processing.

[12]  Otilia Popescu,et al.  Game-Theoretic Approach to Joint Transmitter Adaptation and Power Control in Wireless Systems , 2010, IEEE Transactions on Systems, Man, and Cybernetics, Part B (Cybernetics).

[13]  Dimitrie C. Popescu,et al.  Joint transmitter adaptation and power control for downlink wireless systems with target SIR requirements , 2011, 2011 45th Annual Conference on Information Sciences and Systems.

[14]  Octavia A. Dobre,et al.  Joint transmitter adaptation and power control in multi-user wireless systems with target SIR requirements , 2010, 2010 Conference Record of the Forty Fourth Asilomar Conference on Signals, Systems and Computers.

[15]  Linda Doyle,et al.  GUEST EDITORIAL - COGNITIVE RADIOS FOR DYNAMIC SPECTRUM ACCESS , 2007 .

[16]  Ananthanarayanan Chockalingam,et al.  Precoder Optimization in Cognitive Radio with Interference Constraints , 2011, 2011 IEEE International Conference on Communications (ICC).

[17]  Robert W. Heath,et al.  Exploiting limited feedback in tomorrow's wireless communication networks , 2008, IEEE Journal on Selected Areas in Communications.

[18]  Jaap van de Beek Sculpting the multicarrier spectrum: a novel projection precoder , 2009, IEEE Communications Letters.

[19]  Sergio Barbarossa,et al.  Cognitive MIMO radio , 2008, IEEE Signal Processing Magazine.

[20]  Joseph Mitola,et al.  Cognitive radio: making software radios more personal , 1999, IEEE Wirel. Commun..