Adaptive Linear Turbo Equalization Over Doubly Selective Channels

摘要

Over the last decade, tremendous gains, leading to near-capacity achieving performance, have been shown for a variety of communication systems through the application of the turbo principle, i.e., the exchange of extrinsic information between constituent algorithms for tasks such as channel decoding, equalization, and multiple-input–multiple-output (MIMO) detection. In this paper, we study the practical application of such an iterative detection and decoding (IDD) framework to underwater acoustic communications. We explore complexity and performance tradeoffs of a variety of turbo equalization (TEQ)-based receiver architectures. First, we elaborate on two popular but suboptimal turbo equalization techniques: a channel-estimate-based minimum mean-square error TEQ (CE-based MMSE-TEQ) and a direct-adaptive TEQ (DA-TEQ). We study the behavior of both TEQ approaches in the presence of channel estimation errors and adaptive filter adjustment errors. We confirm that after a sufficient number of iterations, the performance gap between these two TEQ algorithms becomes small. Next, we demonstrate that an underwater receiver architecture built upon the least mean squares (LMS) DA-TEQ technique can leverage and dramatically improve the performance of the conventional implementation based on the decision-feedback equalizer at a feasible complexity. To maintain performance gains over time-varying channels, the slow convergence speed of the LMS algorithm has been improved via two methods: 1) repeating the weight update for the same set of data with decreasing step size and 2) reducing the dimensionality of the equalizer by capturing sparse channel structure. This receiver architecture was used to process collected data from the SPACE 08 experiment (Martha's Vineyard, MA). Receiver performance for different modulation orders, channel codes, and hydrophone configurations is examined at a variety of distance, up to 1 km from the transmitters. Experimental results show great -n-npromise for this approach, as data rates in excess of 15 kb/s could readily be achieved without error.