In the next generation of wireless systems, Massive MIMO offers high angular resolution for localization. By virtue of large number of antennas, the Angle of Arrival (AoA) of User Terminals (UTs) can be estimated with high accuracy. According to Dense Multipath Component (DMC) channel model, local scatters around UTs can create different multipath signals for each antenna at the Base Station (BS). We obtain a deterministic form for the Cramer-Rao Lower Bound (CRLB) in a multi-user scenario when the contribution of the multipath signals is considered. We do this when the multipath signals are independent and identically distributed (i.i.d) with arbitrary distribution. Then, we redefine a localization efficiency function for a multi-user scenario and numerically optimize it with respect to (w.r.t) the number of antennas. We prove when only a subset of the available antennas is used, CRLB can be minimized w.r.t which set of antennas is used. Then, an antenna selection strategy that minimizes CRLB is proposed. As a benchmark, we apply the proposed antenna selection scheme to the MUltiple SIgnal Classification (MUSIC) algorithm and study its efficiency. Numerical results validate the accuracy of our analysis and show significant improvement in efficiency when the proposed antenna selection strategy is employed.
翻译:在下一代无线系统中,MIMIMM为本地化提供了高角分辨率。 由于天线数量众多, 用户终端( UTs) 的“ 抵达角( AoA) ” 可以用高精度来估算。 根据 Dense 多路传输组件( DMC) 频道模型, 围绕 UTs 的本地散射可以为基地站的每个天线创建不同的多路信号。 当考虑多路信号的贡献时, 我们在一个多用户假设中为 Cramer- Rao Lower Bound( CRLB) 获得一种确定形式。 当多路信号是独立且分布相同( i.d) 的多路信号时, 我们这样做。 然后, 我们重新定义一个多路信号的本地化效率功能功能功能, 并在( w.r.t.) 天线上进行数字优化。 我们证明, 当只使用可用的天线的一个子子子组, 我们就可以将设置天线的网络选择战略最小化 w.r. t。 然后, 我们提出的天线选择战略, 将CRLB 和SICMLMLVI 的精确度选择方案作为基准, 用于SICLPLValalalalalalalalal 的精确度测试方案的基准, 。