A Low Complexity Iterative Receiver for High Spectral-Efficiency Battlefield MIMO Communications

Abstract

For multiple-input multiple-output (MIMO) systems, space-time bit-interleaved coded modulation (STBICM) using iterative detection has been recognized as a method to achieve near-capacity performance. However, the a posteriori probability (APP) detector required for this near-optimal performance exhibits prohibitive implementation complexity at high rates (≥16 coded bps/Hz) due to its exponential complexity in rate. With a view to enabling practical implementations of high spectral-efficiency wireless communications, this paper introduces a singlestream detection approach using spatial-filtering (or nulling) and soft-cancellation. Relative to the conventional APP detector, the proposed method is shown to have a superior performance-complexity trade. This paper also demonstrates the robustness of the proposed single-stream detection approach in overloaded conditions where there are fewer receive antenna elements devoted to signal separation than there are transmitted streams.

Decoding-Aided Parameter Estimation for Interference Cancellation and Suppression Receivers in LTE-Advanced Systems

“…In this paper, for estimating the interference parameters, we adopt the simplest similarity criterion based on the least squares fit, i.e., It should be noted that due to non-ideal signal reconstruction, the residual errors after the compensation step should be taken into account in the interfering signal estimation algorithm by including in matrix ( ) 2 2 , β w R ni the covariance matrix of the soft symbol estimation error calculated as follows [11][12] Here 1 e is the estimated value of the error power which is obtained as follows: …”

High accuracy, low complexity performance prediction in adaptive MIMO systems

“…But, equations (4), (5), (6), and (8), require hundreds and even thousands of double integrals. We reduce this complexity first by reducing the computational burden of the PEP, and then by computing a minimal number of PEPs.…”

A low complexity MIMO detector based on combination of MRC and MMSE algorithm

“…K-best algorithm has the nature to generate the candidate list for soft output, however, it needs large K to guarantee performance in bit error rate (BER) when high order modulation is considered, which will introduce high computational complexity [4]. Due to the property of Gaussian output, a low complexity detector based on MMSE algorithm is proposed for coded systems [5], [6], where the symbols from different transmit antennas are first decoupled and then the corresponding soft information associated with its symbol is calculated to be fed to the soft decoder. For the determined system, MMSE-based detector can reach ML's performance in limited iterations, but when the underdetermined system is considered, group-wise MMSE-based detector should be utilized to get tradeoffs between performance and complexity [6].…”