Abstract

This paper considers a cognitive radio (CR) network, in which the unlicensed (secondary) users (SUs) are allowed to concurrently access the spectrum allocated to the licensed (primary) users, provided that the interference of SUs with the primary users (PUs) satisfies certain constraints. It is more general and owns a stronger challenge to ensure the quality of service (QoS) of PUs, as well as to maximize the sum-rate of SUs. On the other hand, the multiple-antenna mobile user case has not been well investigated for the target problem in the open literature. We refer to this setting as multiple input multiple output multiple access channels (MIMO-MAC) in the CR network. Subject to the interference constraints of SUs and the peak power constraints of SUs, the sum-rate maximization problem is solved. To efficiently maximize the achievable sum-rate of SUs, a tight pair of upper and lower bounds, as an interval, of the optimal Lagrange multiplier is proposed. It can avoid ineffectiveness or inefficiency when the dual decomposition is used. Furthermore, a novel water-filling-like algorithm is proposed for the inner loop computation of the proposed problem. It is shown that this algorithm used in the inner loop computation can obtain the exact solution with a few finite computations, to avoid one more loop, which would be embedded in the inner loop. In addition, the proposed approach overcomes the limitation of Hermitian matrices, as optimization variables. This limitation to the optimization problem in several complex variables has not been well investigated so far. As a result, our analysis and results are solidly extended to the field of complex numbers, which are more compatible with practical communication systems.

Highlights

  • The radio spectrum is a precious resource that needs careful planning, as the currently licensed spectrum is severely underutilized [1]

  • Since the multiple-input multiple-output (MIMO) technology uses multiple antennas at both the transmitter and the receiver to significantly increase data throughput and link range without additional bandwidth or transmit power, it plays an important role in wireless communications today

  • Since there is no existing method to compute the maximum sum-rate of the MIMO MAC in the Cognitive radio (CR) networks, we made some development to the iterative water-filling-like algorithm in [6] to solve the target problem for comparison purposes

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Summary

Introduction

The radio spectrum is a precious resource that needs careful planning, as the currently licensed spectrum is severely underutilized [1]. Cognitive radio (CR) [2], which adapts the radio’s operating characteristics to the real-time conditions, is the key technology that allows flexible, efficient and reliable spectrum utilization to be realized in wireless communications. This technology exploits the facts that the licensed spectrum is underutilized by the primary user(s) (PU), and it introduces the secondary user(s). For the SIMO-MAC in CR networks, as a special case of the MIMO-MAC in CR networks, the weighted sum-rate maximization problem has been investigated in [7] to compute the optimal power allocation. Si λ water level step (highest step under water) expectation on probability total number of channels upper bound for total power or sum-power upper bound for the peak power constraint at step k trace operation of a square matrix signal transmitted by the i-th SU, which is a column vector

MIMO-MAC in a CR Network and Its Sum-Rate
Algorithm ALW1
Convergence of Algorithm ALW1
Performance Results and Comparison
Conclusions
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