Reconfigurable Adaptive Singular Value Decomposition Engine Design for High-Throughput MIMO-OFDM Systems

Abstract

Singular value decomposition (SVD) is an optimal method to obtain spatial multiplexing gain in multi-input multi-output (MIMO) channels. However, the high cost of implementation and high decomposing latency of the SVD restricts its usage in current wireless communication applications. In this paper, we present a complete adaptive SVD algorithm and a reconfigurable architecture for high-throughput MIMO-orthogonal frequency division multiplexing systems. There are several proposed architectural design techniques: reconfigurable scheme, division-free adaptive step size scheme, early termination scheme, and data interleaving scheme. The reconfigurable scheme can support all antenna configurations in a MIMO system. The division-free adaptive step size and early termination schemes are used to effectively reduce the decomposing latency and improve hardware utilization. The data interleaving scheme helps to deal with several channel matrices concurrently. Besides, we propose an orthogonal reconstruction scheme to obtain more accurate SVD outputs, and then the system performance will be greatly enhanced. We apply our SVD design to the IEEE 802.11 n applications. This design is implemented and fabricated in UMC 90 nm 1P9M CMOS technology. The maximum operating frequency is measured to be at 101.2 MHz, and the corresponding power dissipation is at 125 mW. The core size is 2.17 mm2 and the die size occupies 4.93 mm2. The chip result shows that the average latency is only 0.33% of the wireless local area network coherence time. Hence, the proposed reconfigurable adaptive SVD engine design is very suitable for high-throughput wireless communication applications.