[Paper Review] Fixed Point Realization of Iterative LR-Aided Soft MIMO Decoding Algorithm

Mehnaz Rahman, Gwan Choi|arXiv (Cornell University)|Mar 31, 2015

Advanced Wireless Communication Techniques21 references3 citations

TL;DR

This paper presents a fixed-point implementation of an iterative LR-aided soft MIMO decoding algorithm using a K-best detector to reduce complexity while maintaining near-Maximum Likelihood performance. Simulations show that a 16-bit fixed-point format achieves BER degradation within 0.3 dB for 8x8 MIMO systems across various modulation schemes, enabling efficient hardware deployment with minimal performance loss.

ABSTRACT

Multiple-input multiple-output (MIMO) systems have been widely acclaimed in order to provide high data rates. Recently Lattice Reduction (LR) aided detectors have been proposed to achieve near Maximum Likelihood (ML) performance with low complexity. In this paper, we develop the fixed point design of an iterative soft decision based LR-aided K-best decoder, which reduces the complexity of existing sphere decoder. A simulation based word-length optimization is presented for physical implementation of the K-best decoder. Simulations show that the fixed point result of 16 bit precision can keep bit error rate (BER) degradation within 0.3 dB for 8x8 MIMO systems with different modulation schemes.

Motivation & Objective

• To reduce the hardware complexity of MIMO detection while maintaining near-Maximum Likelihood performance.
• To enable practical physical implementation of iterative soft decision-based LR-aided K-best decoding through fixed-point arithmetic.
• To optimize word length for fixed-point representation to minimize BER degradation in MIMO systems.
• To evaluate the performance of fixed-point implementation across different modulation schemes and MIMO configurations.
• To demonstrate feasibility of 16-bit fixed-point precision for 8x8 MIMO systems with minimal performance loss.

Proposed method

• Designing a fixed-point representation of the iterative LR-aided soft MIMO decoding algorithm using Q15 format for 16-bit precision.
• Applying lattice reduction (LR) to transform the MIMO detection problem into a more favorable form for K-best detection.
• Implementing an iterative soft decision feedback mechanism to refine reliability estimates in successive interference cancellation.
• Using simulation-based word-length optimization to determine optimal bit-widths for internal data paths.
• Employing a K-best sphere decoding algorithm with fixed-point arithmetic to reduce computational complexity.
• Validating the design across multiple modulation schemes (e.g., QPSK, 16-QAM) in 8x8 MIMO configurations.

Experimental results

Research questions

• RQ1 Can a fixed-point implementation of an iterative LR-aided K-best MIMO decoder achieve near-ML performance with reduced complexity?
• RQ2 What is the minimum word length required to maintain acceptable BER degradation in 8x8 MIMO systems?
• RQ3 How does the BER performance of the fixed-point design compare to the floating-point reference across different modulation schemes?
• RQ4 To what extent does lattice reduction improve the performance of fixed-point K-best decoding in MIMO systems?
• RQ5 Can the proposed fixed-point design be practically deployed in hardware with minimal performance loss?

Key findings

• A 16-bit fixed-point implementation achieves BER degradation of less than 0.3 dB compared to the floating-point reference in 8x8 MIMO systems.
• The fixed-point design maintains near-Maximum Likelihood performance across various modulation schemes, including QPSK and 16-QAM.
• Word-length optimization through simulation significantly reduces hardware complexity without substantial performance loss.
• The iterative soft decision feedback mechanism enhances reliability and convergence in the fixed-point decoding chain.
• The proposed method enables efficient hardware realization of K-best decoding with low area and power consumption.
• The results demonstrate the feasibility of deploying 16-bit fixed-point arithmetic in high-rate MIMO systems with minimal performance degradation.