A Distributed Power Allocation Scheme for Sum-Rate Maximization on Cognitive GMACs | IEEE Journals & Magazine | IEEE Xplore

A Distributed Power Allocation Scheme for Sum-Rate Maximization on Cognitive GMACs


Abstract:

This paper considers a distributed power allocation scheme for sum-rate-maximization under cognitive Gaussian multiple access channels (GMACs), where primary users and se...Show More

Abstract:

This paper considers a distributed power allocation scheme for sum-rate-maximization under cognitive Gaussian multiple access channels (GMACs), where primary users and secondary users may communicate under mutual interference with the Gaussian noise. Formulating the problem as a standard nonconvex quadratically constrained quadratic problem (QCQP) provides a simple distributed method to find a solution using iterative Jacobian method instead of using centralized schemes. A totally asynchronous distributed power allocation for sum-rate maximization on cognitive GMACs is suggested. Simulation results show that this distributed algorithm for power allocation converges to a fixed point and the solution achieves almost the same performance as the exhaustive search.
Published in: IEEE Transactions on Communications ( Volume: 61, Issue: 1, January 2013)
Page(s): 248 - 256
Date of Publication: 06 February 2013

ISSN Information:


I. Introduction

Investigation of both spatial and temporal spectrum utilization reveals the fact that not all the spectrum is in use all the time. Cognitive radio technology inspired by the observation turns out to be a promising technique for the efficient use of this unused spectrum, potentially allowing a large amount of spectrum to become available for future high bandwidth applications [1] [9]. Some works [2]–[5] make discussions on cognitive radio's achievable rate from information theoretic point. In the seminal work [3], the achievable rate of a single cognitive radio user is provided under such constraints as (i) there is no interference to the primary user, and (ii) the primary encoder-decoder pair is oblivious to the presence of cognitive radio. In [4], they extend the result of [3] to the case with multiple cognitive radio users and characterize the cognitive radio's achievable rate region for Gaussian multiple access channels (MACs). Maximization of the cognitive radio's sum-rate on Gaussian MAC then raises the problem of the allocation of each cognitive user's power ratio [5].

References

References is not available for this document.