Abstract
We propose a loop-reduction LLL (LR-LLL) algorithm for lattice-reduction-aided (LRA) multi-input multioutput (MIMO) detection. The LLL algorithm is an iterative algorithm that contains many check and process operations; however, the traditional LLL algorithm itself possesses a lot of redundant check operations. To solve this problem, we propose a look-ahead check technique that not only reduces the complexity of the LLL algorithm but also produces the lattice-reduced matrix which obeys the original LLL criterion. Simulation results show that the proposed LR-LLL algorithm reduces the average number of loops or computation complexity. Besides, it also shortens the latency <i >of clock cycles</i> about 19.4%, 29.1%, and 46.1% for <svg style="vertical-align:-0.3135pt;width:32.700001px;" id="M1" height="11.075" version="1.1" viewBox="0 0 32.700001 11.075" width="32.700001" xmlns="http://www.w3.org/2000/svg"> <g transform="matrix(1.25,0,0,-1.25,0,11.075)"> <g transform="translate(72,-63.14)"> <text transform="matrix(1,0,0,-1,-71.95,63.5)"> <tspan style="font-size: 12.50px; " x="0" y="0">4</tspan> <tspan style="font-size: 12.50px; " x="9.0271664" y="0">×</tspan> <tspan style="font-size: 12.50px; " x="19.804752" y="0">4</tspan> </text> </g> </g> </svg>, <svg style="vertical-align:-0.3135pt;width:32.700001px;" id="M2" height="11.075" version="1.1" viewBox="0 0 32.700001 11.075" width="32.700001" xmlns="http://www.w3.org/2000/svg"> <g transform="matrix(1.25,0,0,-1.25,0,11.075)"> <g transform="translate(72,-63.14)"> <text transform="matrix(1,0,0,-1,-71.95,63.5)"> <tspan style="font-size: 12.50px; " x="0" y="0">8</tspan> <tspan style="font-size: 12.50px; " x="9.0271664" y="0">×</tspan> <tspan style="font-size: 12.50px; " x="19.804752" y="0">8</tspan> </text> </g> </g> </svg>, and <svg style="vertical-align:-0.3135pt;width:48.325001px;" id="M3" height="11.075" version="1.1" viewBox="0 0 48.325001 11.075" width="48.325001" xmlns="http://www.w3.org/2000/svg"> <g transform="matrix(1.25,0,0,-1.25,0,11.075)"> <g transform="translate(72,-63.14)"> <text transform="matrix(1,0,0,-1,-71.95,63.5)"> <tspan style="font-size: 12.50px; " x="0" y="0">1</tspan> <tspan style="font-size: 12.50px; " x="6.2515001" y="0">2</tspan> <tspan style="font-size: 12.50px; " x="15.278666" y="0">×</tspan> <tspan style="font-size: 12.50px; " x="26.056252" y="0">1</tspan> <tspan style="font-size: 12.50px; " x="32.307751" y="0">2</tspan> </text> </g> </g> </svg> MIMO systems, respectively.
Highlights
To increase the transmission capacity, multiple-input multiple-output (MIMO) system has been proposed for the generation wireless communication systems, and the need for a high-performance and low-complexity MIMO detector becomes an important issue
To verify the proposed LLL algorithm, we simulate the LLLaided MIMO detections based on the MIMO system described in Section 2, and we employ sorted QR decomposition in all MIMO detectors
The proposed LLL algorithm can reduce the average number of loops to 93% ∼94% of the original LLL algorithm
Summary
To increase the transmission capacity, multiple-input multiple-output (MIMO) system has been proposed for the generation wireless communication systems, and the need for a high-performance and low-complexity MIMO detector becomes an important issue. The maximum likelihood (ML) detector is known to be an optimal detector; it is impractical for realization owing to its great computational complexity Addressing this problem, researchers have proposed tree-based search algorithms, such as sphere decoding [1] and K-Best decoding [2], to reduce the complexity with near-optimal performance. We propose a look-ahead check technique to detect and avoid the unnecessary check operations in the LLL algorithm. This technique generates the lattice-reduced matrix which obeys the size reduction and LLL reduction in the original LLL algorithm and applies to real- and complex-value LLL algorithm [5].
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