Approximate MIMO Iterative Processing With Adjustable Complexity Requirements

Targeting only the best achievable bit error rate (BER) performance in iterative receivers operating over multiple-input-multiple-output (MIMO) channels may result in a significant waste of resources, particularly when the achievable BER is considerably better than the target performance [e.g., under good channel conditions and at high signal-to-noise ratio (SNR)]. In contrast to the typical iterative schemes, a practical iterative decoding framework that approximates the soft information exchange is proposed, allowing reduced complexity sphere and channel decoding that is adjustable to the transmission conditions and the required BER. With the proposed approximate soft information exchange, the performance of the exact soft information can still be reached with significant complexity reduction.