• Journal of Communications and Networks
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• 제13권5호
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• pp.481-493
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• 2011

Multiple-input multiple-output (MIMO) technology provides high data rate and enhanced quality of service for wireless communications. Since the benefits from MIMO result in a heavy computational load in detectors, the design of low-complexity suboptimum receivers is currently an active area of research. Lattice-reduction-aided detection (LRAD) has been shown to be an effective low-complexity method with near-maximum-likelihood performance. In this paper, we advocate the use of systolic array architectures for MIMO receivers, and in particular we exhibit one of them based on LRAD. The "Lenstra-Lenstra-Lov$\acute{a}$sz (LLL) lattice reduction algorithm" and the ensuing linear detections or successive spatial-interference cancellations can be located in the same array, which is considerably hardware-efficient. Since the conventional form of the LLL algorithm is not immediately suitable for parallel processing, two modified LLL algorithms are considered here for the systolic array. LLL algorithm with full-size reduction-LLL is one of the versions more suitable for parallel processing. Another variant is the all-swap lattice-reduction (ASLR) algorithm for complex-valued lattices, which processes all lattice basis vectors simultaneously within one iteration. Our novel systolic array can operate both algorithms with different external logic controls. In order to simplify the systolic array design, we replace the Lov$\acute{a}$sz condition in the definition of LLL-reduced lattice with the looser Siegel condition. Simulation results show that for LR-aided linear detections, the bit-error-rate performance is still maintained with this relaxation. Comparisons between the two algorithms in terms of bit-error-rate performance, and average field-programmable gate array processing time in the systolic array are made, which shows that ASLR is a better choice for a systolic architecture, especially for systems with a large number of antennas.

• ETRI Journal
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• 제34권4호
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• pp.503-510
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• 2012

We analyze the relationship between channel coherence bandwidth and two complexity-reduced lattice reduction aided detection (LRAD) algorithms for multiple-input multiple-output (MIMO) orthogonal frequency division multiplexing (OFDM) systems in correlated fading channels. In both the adaptive LR algorithm and the fixed interval LR algorithm, we exploit the inherent feature of unimodular transformation matrix P that remains the same for the adjacent highly correlated subcarriers. Complexity simulations demonstrate that the adaptive LR algorithm could eliminate up to approximately 90 percent of the multiplications and 95 percent of the divisions of the brute-force LR algorithm with large coherence bandwidth. The results also show that the adaptive algorithm with both optimum and globally suboptimum initial interval settings could significantly reduce the LR complexity, compared with the brute-force LR and fixed interval LR algorithms, while maintaining the system performance.

• 한국통신학회논문지
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• 제33권11C호
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• pp.932-939
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• 2008

공간 다중화 방식의 MIMO(Multiple-Input Multiple-Output) 시스템에서 MLD(Maximum-Likelihood Detector)는 최적의 성능을 보이지만, 그 복잡성이 상당히 큰 단점이 있다. 이를 보완하기 위해 여러 가지 기법들이 제안되었으며, Lattice-reduction(LR) 검출기 또한 MIMO 시스템의 성능을 개선하기 위해 제안되었다. 본 논문에서는 확장된 잡음분산 행렬을 이용해 rounding operation 과정에서 발생하는 양자화 오류를 이용해 송신 신호 벡터에 근접한 candidate symbol set을 찾고, 여기서 Semidefinite Relaxation을 이용해 최대 우도 symbol을 검출한다. 그러나 그 복잡도는 MLD의 복잡도 보다 현저히 작고, LR 검출기의 복잡도에 근접한다.