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SFIM Detector Based on Joint-Sparse Index Removal for MIMO-OFDM-CR System

机译:SFIM检测器基于联合稀疏指数去除MIMO-OFDM-CR系统

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摘要

This letter proposes a joint-sparse index removal (JSIR) based algorithm to detect the index of space-frequency index modulation (SFIM) signal for MIMO-OFDM cognitive radio (MIMO-OFDM-CR) system. At first, the proposed algorithm calculates the inner-product matrix of the received signal and channel gain to measure the index information of each subcarrier on each antenna. Then, an antenna index metric is computed through a definition which is given by summing the metrics of all subcarriers on the antenna. According to the metric, the silent antenna indices are acquired by comparing the metric with a threshold derived from statistical distribution. Next, the index detection problem is simplified by removing the silent antenna indices, i.e., the joint-sparse indices of SFIM signal matrix. At last, the indices of active subcarriers on active antennas are obtained through solving the simplified problem via a compressed sensing reconstruction algorithm. The complexity analysis shows that the proposed JSIR algorithm has lower complexity under certain conditions, compared with other related methods. The simulation results verify the accuracy of the proposed method in terms of bit error rate (BER).
机译:这封信提出了一种基于联合稀疏指数删除(JSIR)的算法,以检测MIMO-OFDM认知无线电(MIMO-ofdM-CR)系统的空间探测调制(SFIM)信号的索引。首先,所提出的算法计算接收信号的内部产品矩阵和信道增益,以测量每个天线上每个子载波的索引信息。然后,通过通过对天线上所有子载波的度量求和来给出的定义来计算天线索引度量。根据度量,通过将度量与阈值与统计分布的阈值进行比较来获取静默天线指数。接下来,通过删除静默天线索引,即SFIM信号矩阵的联合稀疏指数来简化索引检测问题。最后,通过通过压缩的感测重建算法解决简化的问题来获得有源天线上的有源子载波的索引。复杂性分析表明,与其他相关方法相比,所提出的JSIR算法在某些条件下具有较低的复杂性。仿真结果验证了在误码率(BER)方面所提出的方法的准确性。

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