Title

Throughput optimization for cognitive radios under sensing uncertainty

Document Type

Conference Proceeding

Publication Date

12-1-2010

Abstract

The efficiency of a cognitive radio system depends critically on sensing reliability since post-sensing communication efficiency is subject to optimal resource allocation under this sensing uncertainty. In this paper, we develop online algorithms for maximizing throughput in a cognitive radio when the sensing outcome of the primary channel (available/unavailable) is not always reliable. We first develop a very efficient per-slot power allocation algorithm for a secondary user transmitting under total power constraints over a period ofM time slots, assuming reliable sensing during each slot but with no look-ahead capability. Specifically, we show that it is always possible to achieve a transmission rate that is a constant fraction of the optimal transmission rate even with no apriori knowledge of the number of available slots. Our online power-allocation algorithm is 3:7-competitive, i.e the rate achieved by this algorithm is within a factor of 2:5/ln 2 < 3:7 of the optimal rate that can be achieved by a genie-aided algorithm with full look-ahead knowledge of channel availability during the M slots. Then we analyze the impact of sensing errors on algorithm performance. We show that the online algorithm is still constant-factor competitive with very high probability (≥ 1-1/M) even with sensing errors under the worst-possible input sequence, provided the number of good time slots is reasonably large as a function of M. However, when the number of good time slots is small (Mo(1), for example √M), we show that no online algorithm can achieve a constant-factor competitive ratio. ©2010 IEEE.

Publication Source (Journal or Book title)

Proceedings - IEEE Military Communications Conference MILCOM

First Page

767

Last Page

772

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