CAJ | 학술논문

在多用户M IM O系统下行链路中，块对角化（Block diagonalization ，BD ）预编码算法的和速率性能要优于匹配滤波算法（Matched filter ，MF）和迫零算法（Zero‐forcing ，ZF）。然而，传统的BD算法利用矩阵分解来构造除当前用户的其他所有用户信道的零空间，需要 O（ N2）浮点运算次数（Float point operations ，FLOPs）。当基站的天线数 N趋向于大规模时，BD算法计算复杂度巨大。本文提出一种基于投影子方法构造其他用户合成信道的零空间的BD算法，该算法仅需 O（ N ）FL O Ps。仿真表明：同传统的BD算法相比，本文所提出的低复杂度BD算法显著地降低了实现复杂度，而和速率性能损失微小，仍然优于M F和ZF ，并且当 N趋向于大规模时，它的和速率性能趋向于传统的BD算法和SVD算法。
재다용호M IM O계통하행련로중，괴대각화（Block diagonalization ，BD ）예편마산법적화속솔성능요우우필배려파산법（Matched filter ，MF）화박령산법（Zero‐forcing ，ZF）。연이，전통적BD산법이용구진분해래구조제당전용호적기타소유용호신도적령공간，수요 O（ N2）부점운산차수（Float point operations ，FLOPs）。당기참적천선수 N추향우대규모시，BD산법계산복잡도거대。본문제출일충기우투영자방법구조기타용호합성신도적령공간적BD산법，해산법부수 O（ N ）FL O Ps。방진표명：동전통적BD산법상비，본문소제출적저복잡도BD산법현저지강저료실현복잡도，이화속솔성능손실미소，잉연우우M F화ZF ，병차당 N추향우대규모시，타적화속솔성능추향우전통적BD산법화SVD산법。
In multi‐user MIMO downlink with multi‐antennas at user terminals ,the block diagonalization (BD) precoder obtains a better sum‐rate performance than matched filter (MF) and zero‐forcing (ZF) , thus becomeing an attractive precoder .However ,the conventional BD generates the null space for all channel matrices excluding the current user by using singular‐value decomposition (SVD ) and requires float point operations (FLOPs) of order O(N2 ) .As the antennas number N at base station (BS) tends to be a large‐scale one ,computational complexity increases sharply on BS .Thus ,a novel low‐complexity implementation for BD with a complexity of order O(N) FLOPs is proposed ,where the null space of oth‐er users′channel matrices is constructed by a projection matrix .Simulation and analysis exhibit that the proposed low‐complexity BD significantly reduce the complexity ,compared with the conventional BD and regularized block diagonalization(RBD) at the cost of a slight sum‐rate loss .The algorithm performs bet‐ter than MF and ZF .Meanwhile ,the sum‐rate performance is similar to the conventional BD and SVD as N approaches a large scale number .