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This paper presents a pipelined MIMO detector designed for 4×4 16-QAM spatial multiplexing systems. A modified Dijkstra's algorithm and a pre-calculation technique are proposed to improve the throughput up to 2.6Gb/s, and the Euclidean norm computation is approximated to reduce the chip area without degrading the error-rate performance. The entire detector occupies 1.56mm2 in a 0.18μm CMOS process,...
It is known that MIMO detectors performance is highly influenced by the channel matrix condition number. An efficient way to decrease the channel matrix condition number is the use of Lattice Reduction techniques. In this paper a Lattice-Reduction-Aided (LRA) K-Best detector based on the channel matrix condition number is proposed for improving the performance of conventional K-Best algorithm. This...
In this paper, we propose a low-complexity constant-throughput LLL algorithm for lattice-reduction-aided (LRA) multi-input multi-output (MIMO) detection. The traditional LLL algorithm for the lattice reduction has a drawback of varying throughput due to the variable iteration loops for the size-reduction and LLL-reduction checks. To address this problem, we propose a constant-throughput LLL (CT-LLL)...
Maximum-likelihood detection (MLD) is the optimal scheme for multiple-input multiple-output (MIMO) channels. However, due to its exponentially high complexity, many alternative algorithms, including some parallel detection (PD) ones with low complexity and high stability, have been proposed for practical applications. Nevertheless, the existing PD algorithms are unable to exploit sufficiently the...
MIMO-OFDM schemes with SDM have been studied for high speed multimedia systems. However, since accurate received MIMO signal detection is very hard, MIMO-OFDM systems have not reached the available capacities. For high detection performance and low complexity, we propose efficient K-best detection technique. The proposed technique increases the detection performance by using OSIC scheme for initial...
It is well known that the maximum-likelihood (ML) detection for multiple-input-multiple-output (MIMO) systems requires high computational complexity. As a result, many suboptimal algorithms, achieving a tradeoff between computational complexity and performance, have been proposed. Among these algorithms, the sphere decoding (SD) detector is considered as a very efficient solution. However, the throughput...
In this paper, we will present a near-ML (maximum likelihood) MIMO (multiple input multiple output) detector explicitly optimized for parallel programmable baseband architectures, such as DSPs (digital signal processors) with VLIW (very long instruction word), SIMD (single instruction multiple data) or vector processing features. First, we propose the SSFE (selective spanning with fast enumeration)...
The complex sphere decoding algorithm has optimal bit error ratio performance for uncoded multiple-input multiple-output (MIMO) systems. The computational and hardware complexities of this algorithm increase significantly for detection of 64-QAM modulated signal streams. In this paper two modifications to the original sphere decoding algorithm are proposed that reduce both computational complexity...
In this paper, an adaptive detection technique for MIMO-OFDM system is proposed. To execute the adaptive detection, existing SMLD technique is considered. The proposed technique selects proper values of V of the SMLD scheme to each subcarrier according to its estimated received power. To estimate the received power, two estimation modes are presented (noise value estimation mode with a preamble and...
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