Abstract View

Systolic Arrays for Lattice-Reduction-Aided MIMO Detection

Multiple-inputmultiple-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. Latticereduction- 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¢„asz (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¢„asz 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.