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The integer-forcing (IF) linear multiple-input and multiple-output (MIMO) receiver is a recently proposed suboptimal receiver which nearly reaches the performance of the optimal maximum likelihood receiver for the entire signal-to-noise ratio (SNR) range and achieves the optimal diversity multiplexing tradeoff for the standard MIMO channel with no coding across transmit antennas in the high SNR regime...
We propose a lattice-reduction-aided sphere decoding (SD) algorithm for MIMO detection achieving exact maximum likelihood (ML) detection performance with very low computational complexity in the mid and high signal-to-noise ratio (SNR) regions. A simple criterion is presented to determine if the ML detection result is obtained by a primary search. If not, a further search will be carried out to find...
The sphere decoding (SD) algorithm based on Schnorr-Euchner (S-E) strategy can reduce the complexity for multiple-input multiple-output (MIMO) systems to find the maximum likelihood (ML) solution by updating the search radius whenever a new lattice point was found. In this paper, we propose an improved scheme to reduce the complexity of sphere decoding. In the new method, a factor was introduced for...
Sphere detection and Ordered Successive Interference Cancellation (OSIC) technologies are the most important techniques in multiple input multiple output (MIMO) detection. In this paper, a hierarchical MIMO detection technology which combines OSIC with K-Best SE algorithm is proposed. The proposed algorithm distributes layers into the two detect techniques and adjusts the ratio based on Channel Gain...
The ordering of the columns of the channel matrix has a deep impact in the performance of many decoding methods for MIMO problems. The most popular algorithms for computation of good orderings use as only input the channel matrix (such as the V-BLAST ordering). However, there are other interesting algorithms that compute the ordering as a function of the matrix and of the signal to be decoded. Here...
Maximum-likelihood detection in MIMO communications amounts to solving a least-squares problem with a constellation (alphabet) constraint. One popular method that can be used to solve this problem is sphere decoding. We show in this letter that by employing a simple stopping criterion, it is possible to significantly reduce the complexity of sphere decoding over a wide range of SNRs, without a noticeable...
Many powerful data detection algorithms employed in multiple-input multiple-output (MIMO) communication systems, such as sphere decoding (SD) and lattice-reduction (LR)-aided detection, were initially designed for infinite lattices. Detection in MIMO systems is, however, based on finite lattices. In this paper, we systematically study the consequences of finite lattice-size for the performance and...
In this paper, we propose a near maximum likelihood (ML) decoding technique, which reduces the computational complexity of the exact ML decoding algorithm. The computations needed for the tree search in the ML decoding is simplified by reducing the dimension of the search space prior to the tree search. In order to compensate performance loss due to the dimension reduction, a list stack algorithm...
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