Papers by Keyword: Antenna Selection

Abstract: The antenna number in distributed MIMO system is much larger than that in distributed antenna system (DAS) and traditional centralized MIMO system. Therefore adopting the existing antenna selection algorithms with excellent performance will make it difficult to realize the system due to the complexity of the algorithms. In order to solve the problem, a novel antenna selection algorithm performed at the base station (BS) is proposed according to the structural characteristics of the system. In the proposed algorithm, the antenna search scope is narrowed down by port selection based on the trace of the sub-channel matrices, and antennas with little contributions to the system capacity are removed gradually by iteratively updating the optimization parameter, which further reduces the complexity. When this algorithm is treated as the transmit antenna selection algorithm, its port selection process is performed by the user equipment, which can reduce the feedback overhead. Simulation results show that the proposed algorithm possesses the similar system capacity with the optimal algorithm.

Abstract: Using multiple antennas in coexisting radio systems can cancel or control the co-channel interference and hence improves the overall spectrum efficiency. However, the hardware complexity and costs limit the usage of multiple-antenna technology. Antenna selection may reduce such costs while partly remaining the advantage of the multiple-antenna technology. In this paper, a fixed power cognitive radio system model jointly combined with antenna selection and users selection is set up. And the mathematical closed-form expressions of the channel capacity and bit error rate (BER) are obtained through mathematical derivation. Simulation verifies the correctness of theoretical results and shows that the system exists an optimal transmit power which optimizes the system performance. Furthermore, the influences of users number and antennas number on the system performance have been studied.

Abstract: To protect the primary user and improve the credibility of spectrum sensing, a spectrum sensing optimization algorithm based on antenna selection is proposed in this paper. In the case where the channel coefficient and signal-to-noise ratio are not known, one antenna weighting and selection algorithm based on auto-correlation is proposed. This algorithm can also be used to distinguish whether it is necessary for antennas selection so as to optimize spectrum sensing performance. Based on auto-correlation ratio, selecting parts of the antennas to cooperatively sense spectrum can maximize the detection probability. Simulations are used to verify the method. The results indicate that the proposed antenna weighting and selection algorithm can be able to optimize network performance.

Abstract: The antenna diversity based on log-likelihood ratio (LLR) is better than that based on signal-to-noise ratio (SNR) in bit error rate performance for MIMO systems. Thus in this paper, we present a novel transmit antenna selection scheme based on bit log-likelihood ratio when the Alamouti code is employed .Then the BER expressions of application based on Bit-LLR (BLLR) for MPSK and MQAM modulation with Gray code are derived. The simulation results show that the new scheme based on BLLR is superior to SNR. With the increase of the transmit antennas, the performance of system is improved significantly. Furthermore, the diversity order is the same as that of the full complexity systems.

Abstract: Multiple-input multiple-output (MIMO) systems can bring many advantages to wireless communication but suffer from high cost and complexity due to the multiple RF chains. In such systems, antenna selection is introduced as a technique to ease these problems.This paper addressedthe problem of antenna selection in spatially correlated channels. We propose an effective antenna selection method in terms of capacity maximization based on the transmit and/or the receive correlation matrix instead of the instantaneous channel state information (ICSI).Simulations will be used to validate our analysis and demonstrate that the number of required RF chains can be significantly decreased using our low complexity algorithm whileachieving very close performance to the ICSI-based method.