Optimized Configurable Architectures for Scalable Soft-Input Soft-Output MIMO Detectors with 256-QAM
Mohammad M. Mansour, Louay M.A. Jalloul

TL;DR
This paper introduces an optimized, high-throughput MIMO detector architecture supporting up to 4 layers and 256-QAM, with low complexity and reconfigurability for iterative detection and decoding in wireless systems.
Contribution
It proposes a novel low-complexity, configurable MIMO detector core that efficiently handles multiple layers and high-order modulation, optimized for area and throughput.
Findings
Achieves 733 Mbps throughput with 256-QAM in 90 nm CMOS
Supports up to 4 layers with near-optimal performance
Reduces complexity by eliminating multipliers and optimizing slicing
Abstract
This paper presents an optimized low-complexity and high-throughput multiple-input multiple-output (MIMO) signal detector core for detecting spatially-multiplexed data streams. The core architecture supports various layer configurations up to 4, while achieving near-optimal performance, as well as configurable modulation constellations up to 256-QAM on each layer. The core is capable of operating as a soft-input soft-output log-likelihood ratio (LLR) MIMO detector which can be used in the context of iterative detection and decoding. High area-efficiency is achieved via algorithmic and architectural optimizations performed at two levels. First, distance computations and slicing operations for an optimal 2-layer maximum a posteriori (MAP) MIMO detector are optimized to eliminate the use of multipliers and reduce the overhead of slicing in the presence of soft-input LLRs. We show that…
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