Conference Paper

Reduced-Complexity Power-Efficient Wireless OFDMA using an Equally Probable CSI Quantizer

Univ. Rey Juan Carlos. Fuenlabrada, Madrid
DOI: 10.1109/ICC.2007.484 Conference: Communications, 2007. ICC '07. IEEE International Conference on
Source: IEEE Xplore

ABSTRACT Emerging applications involving low-cost wireless sensor networks motivate well optimization of multi-user orthogonal frequency-division multiple access (OFDMA) in the power-limited regime. In this context, the present paper relies on limited- rate feedback (LRF) sent from the access point to terminals to acquire quantized channel state information (CSI) in order to minimize the total average transmit-power under individual average rate and error probability constraints. Specifically, we introduce two suboptimal reduced-complexity schemes to: (i) allocate power, rate and subcarriers across users; and (ii) design accordingly the channel quantizer. The latter relies on the solution of (i) to design equally probable quantization regions per subcarrier and user. Numerical examples corroborate the analytical claims and reveal that the power savings achieved by our reduced-complexity LRF designs are close to those achieved by the optimal solution.

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    ABSTRACT: The present paper deals with dynamic resource management based on quantized channel state information (CSI) for multi-carrier cognitive radio networks comprising primary and secondary wireless users. For each subcarrier, users rely on adaptive modulation, coding and power modes that they select in accordance with the limited-rate feedback they receive from the access point. The access point uses CSI to maximize the sum of generic concave utilities of the individual average rates in the network while respecting rate and power constraints on the primary and secondary users. Using a stochastic dual approach, optimum dual prices are found to optimally allocate resources across users per channel realization without requiring knowledge of the channel distribution.
    Proceedings of the IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2008, March 30 - April 4, 2008, Caesars Palace, Las Vegas, Nevada, USA; 01/2008

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