A New Lattice Reduction Algorithm for LR-Aided MIMO Linear Detection

Abstract

Abstract-Lattice reduction (LR) has recently emerged as a promising technique for improving the performance of suboptimal multiple-input-multiple-output (MIMO) detectors. For LRaided MIMO detection, the Lenstra-Lenstra-Lovász (LLL) and Seysen's algorithm (SA) have been considered almost exclusively to date. In this paper, we introduced a new LR algorithm for LR-aided linear detection (LD). In contrast to the LLL and SA, which are targeted to search for bases with relatively short basis vectors, the proposed algorithm has been designed to improve the minimum Euclidean distance of the LR-aided linear detector, thus exhibiting improved error rate at high SNR. The error-rate performance of the proposed algorithm as well as the required complexity has been demonstrated through extensive computer simulations.

An improved scheme based on log-likelihood-ratio for lattice reduction-aided MIMO detection

“…The elements of the transmitted signal are drawn from the MQAM constellation. The signal to noise ratio (SNR) is defined as the average received energy per information bit divided by σ 2 [15,17]. Our LLL-LLR and Table 1 The description of the LLR-based TA in ZF criterion Using (38) to obtain λ * k,i and get…”

“…Recently, an efficient scheme called lattice reduction [14][15][16][17][18] has been shown great potential in MIMO detections. The lattice reduction (LR) algorithm attempts to change the orthogonality of the channel matrix, as the orthogonality of the channel matrix largely affects the performance of the MIMO system [15].…”

“…Many LR algorithms have been developed to improve the performance of the LLL algorithm. The LR algorithm improving the minimum Euclidean distance of the LR-aided LDs, which can improve the BER performance of the LR-aided LDs, is proposed in [17]. Element-based lattice reduction (ELR) algorithm [15], a low complexity LR algorithm, was proposed to reduce the diagonal elements of the noise covariance matrix.…”