Abstract
For Massive multiple-input multiple output (MIMO) systems, many algorithms have been proposed for detecting spatially multiplexed signals, such as reactive tabu search (RTS), minimum mean square error (MMSE), etc. As a heuristic neighborhood search algorithm, RTS is particularly suitable for signal detection in systems with large number of antennas. In this paper, we propose a strategy to reduce the neighborhood searching space of the traditional RTS algorithms. For this, we introduce a constellation constraints (CC) structure to determine whether including a candidate vector into the RTS searching neighborhood. By setting a pre-defined threshold on the symbol constellation, the Euclidean distance between the estimated signal and its nearest constellation points are calculated, and the threshold and distance are compared to separate the reliable estimated signal from unreliable ones. With this structure, the proposed CC-RTS algorithm may ignore a significant number of unnecessary candidates in the RTS neighborhood searching space and greatly reduce the computational complexity of the traditional RTS algorithm. Simulation results show that the BER performance of the proposed CC-RTS algorithm is very close to that of the traditional RTS algorithm, and with about 50% complexity reduction with the same signal-to-noise (SNR) ratio.
Highlights
The utilization of spatial multiplexed multiple-input multiple-output (MIMO) technology could linearly increase the link capacity of the communication systems without sacrificing spectrum and time resource [1,2]
We will shown the advantages of constellation constraints (CC)-reactive tabu search (RTS) algorithm in terms of computational complexity and BER performance
We set up a simulation model with the following parameters: the system is a multiple-input multiple output (MIMO) using quadrature phase shift keying (QPSK) modulation with 4 × 4, 8 × 8, 16 × 16, 24 × 24 MIMO antennas
Summary
The utilization of spatial multiplexed multiple-input multiple-output (MIMO) technology could linearly increase the link capacity of the communication systems without sacrificing spectrum and time resource [1,2]. In massive MIMO systems, the total number of antenna elements at user terminals are relatively small This ensures satisfactory performance with simpler signal detection techniques. Massive MIMO is regarded as a core technology for the generation mobile communication systems [1] Harnessing such benefits of large-dimensions in practice, is challenging. In traditional RTS algorithm, the number of candidates involved in the calculation determines the complexity and the performance of the detection algorithm. The detection complexity of the RTS algorithm is associated with the number of candidates involved in calculating the ML cost for each candidate. In this paper, inspired by [14,15], we propose a new scheme which may reducing the RTS complexity by decreasing the searching space of candidates with the help of their estimated reliability.
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