使用不同调制技术的空间复用MIMO-OFDM系统性能测量

Purna Satish A, Tejaswini A, Pavan Kumar Ch, Ashraf A, A. K, K. M
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引用次数: 2

摘要

多输入多输出(MIMO)系统在通信链路两端的每一端采用一个以上的天线,并且可以在单个信道上传输至少两个数据流,而不需要额外的传输容量或功率。为了构建稳定的通信流,接收端通常应该比发射端拥有更多的天线。由于具有更好的表示能力,MIMO框架在过去十年中迅速流行起来。然而,由于远端信道的时间色散特性,在空间复用MIMO系统中会遇到多流干扰和码元间干扰。为了提供可靠和可靠的通信,必须适当地限制干扰对接收方的影响。为了消除空间复用无线信道中的干扰,通常采用正交频分复用(OFDM)技术。研究发现,MIMO和OFDM相结合可以提供更高的生产率、稳定的质量、增益和信息速率,是下一代WLAN和WMANs的一个有吸引力的空中接口建议。因此,本研究开发了一种空间复用MIMO-OFDM系统,并研究了不同调制方式下误码率和比特能量噪声比等性能指标。在接收端,该方法使用零强制均衡器对数据进行空间解复用。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Performance Measures of Spatially Multiplexed MIMO-OFDM System using Different Modulation Techniques
Multiple input multiple output (MIMO) systems employ more than one antenna at each of the two ends of the communication link and may transport at least two data streams over a single channel without requiring additional transmission capacity or power. In order to construct a stable communication stream, the receiving side should often have more antennas than the broadcasting side. Because of their better presentation abilities, MIMO frameworks have quickly gained popularity over the last decade. However, multi-stream interference and inter-symbol interference are encountered in spatially multiplexed MIMO systems as a result of the remote channel’s time-dispersive characteristics. To provide dependable and reliable communication, the influence of interference must be appropriately limited at the recipient. In order to counteract interference in spatially multiplexed wireless channels, orthogonal frequency division multiplexing (OFDM) is usually used. The study found that combining MIMO and OFDM delivers higher productivity, unwavering quality, gain, and information rate, and that it is an appealing air-interface suggestion for next-generation WLAN and WMANs. As a result, a spatially multiplexed MIMO-OFDM system was developed in this study, and performance measures such as bit error rate and bit energy to noise ratio were investigated using various modulation methods. At the receiver, the proposed method uses a zero forcing equalizer to spatially de-multiplex the data.
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