As wireless services proliferate, the demand for available spectrum also grows. As a result, spectral efficiency is still an issue being addressed by many researchers aiming at improving the quality of service to a growing number of users. Massive multiple-input multiple-output (MIMO) has been presented as an attractive technology for the next wireless systems since it can alleviate the expected spectral shortage. Nevertheless, such a technique requires a dedicated chain of radio frequency (RF) components for each antenna element which result in high costs at base station (BS) side. To reduce the number of RF chains, we propose several transmit antenna selection schemes aiming at minimizing the mean square reception error and also reducing the transmission power which is one of the main contributions of our work. The proposed strategies are inspired by the matching pursuit technique and its quantized version, named matching pursuit with generalized bit planes. The presented results show that reliable reception can be accomplished with low computationally intensive algorithms for antenna selection.

中文翻译：

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基于贪心算法的大规模多输入多输出天线选择

随着无线服务的激增，对可用频谱的需求也在增长。因此，频谱效率仍然是许多旨在提高越来越多用户的服务质量的研究人员正在解决的问题。大规模多输入多输出 (MIMO) 已被视为下一代无线系统的一项有吸引力的技术，因为它可以缓解预期的频谱短缺。然而，这种技术需要用于每个天线元件的专用射频 (RF) 组件链，这导致基站 (BS) 侧的成本很高。为了减少射频链的数量，我们提出了几种发射天线选择方案，旨在最小化均方接收误差并降低发射功率，这是我们工作的主要贡献之一。所提出的策略受到匹配追踪技术及其量化版本的启发，称为具有广义位平面的匹配追踪。所呈现的结果表明，可以使用用于天线选择的低计算密集型算法来实现可靠接收。