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Erschienen in:
2016 | OriginalPaper | Buchkapitel
Joint Channel Maximization and Estimation in Multiuser Large-Scale MIMO Cognitive Radio Systems Using Particle Swarm Optimization
verfasst von : Mostafa Hefnawi
Erschienen in: Proceedings of the Mediterranean Conference on Information & Communication Technologies 2015
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Abstract
This paper investigates the use of particle swarm optimization (PSO) for joint channel maximization and estimation in large-scale multiuser multiple-input multiple-output (LS-MU-MIMO) cognitive networks with multiple primary users (PUs) and secondary users (SUs) sharing the same spectrum. The PSO algorithm in this paper is applied at two levels; the mobile station (MS) and the base station (BS). At the MS, PSO is used to seek iteratively the transmit beamforming weights that maximize the uplink MIMO channel capacity for each cognitive user, while controlling the interference levels to PUs without involving any gradient search. At the BS, PSO is used for channel estimation without involving any matrix inversion. The performance of the PSO-based capacity-aware (PSO-CA) cognitive system is compared to the one based on the gradient search scheme (GS-CA) and the results show that PSO-CA requires considerably less computational complexity while achieving essentially the same level of performance as the GS-CA.