Computationally Efficient Multiuser and MIMO Detection based on Dichotomous Coordinate Descent Iterations

The detection in multiuser (MUD) and multiple-input multiple-output (MIMO) systems can increase the spectral efficiency, and therefore is of great interest. Although multiuser and MIMO detection is mature in theory, the real-time implementation is still an open issue. Many suboptimal detection schemes have been proposed, possessing low computational load, but also having poorer detection performance compared to the optimal detector. Multiuser detection can be described as a solution of an optimisation problem; in most cases it is the quadratic optimisation problem. Unconstrained quadratic optimisation is known to result in decorrelating and MMSE multiuser detection, which cannot provide high detection performance. The optimal detection is equivalent to the solution of a constrained problem. However, such detection is too complex for practical systems. In this work, we propose several detectors which possess low complexity and high detection performance. These detectors are based on Dichotomous Coordinate Descent (DCD) iterations, which are multiplication and division free, and therefore are attractive for real-time implementation. We propose a box-constrained DCD algorithm, and apply it to multiuser detection. We also design an FPGA architecture of the box-constrained DCD detector and implement it in an FPGA. This design requires a very small area usage. The fixed-point implementation offers a constant throughput over the signal-to-noise ratio (SNR) and provides almost same detection performance as that of a floating-point implementation. We further exploit the box-constrained DCD algorithm and propose a complex-valued box-constrained DCD algorithm. A box-constrained MIMO detector based on the DCD algorithm shows a better detection performance than the MMSE detector. The proposed FPGA design requires a small area usage, which is significantly less than that required by known designs of the MMSE MIMO detector. Since the box-constrained DCD algorithm could not offer the optimal detection performance, while the sphere decoder encounters high complexity at low SNRs, we suggest a combination of the box-constrained DCD algorithm with the sphere decoder (fast branch and bound algorithm). The combined detection results in reduced complexity at low SNRs while retaining outstanding detection performance at all SNRs. As the box-constrained DCD algorithm is efficient for hardware implementation, we apply it to the nonstationary iterative Tikhonov regularization and propose a DCD-BTN detector. The DCD-BTN detector shows the detection performance very close to the optimal performance. It also shows the lowest complexity among the most advanced detectors. An architecture of the detector has been developed. This detector has been implemented on an FPGA platform. The design requires a small number of FPGA slices. Numerical results have shown that the fixed-point FPGA implementation and a floating-point implementation have similar detection performance. The DCD-BTN detector can only be applied in systems with BPSK modulation. Therefore, we also propose a multiple phase decoder (MPD), which is based on a phase descent search (PDS) algorithm. The PDS algorithm uses coordinate descent iterations, where coordinates are unknown symbol phases, while constraining the symbols to have a unit magnitude. The MPD is investigated in application to detection of M-PSK symbols in multiuser and MIMO systems. In the multiuser detection, the MPD is applied to highly loaded scenarios and numerical results show that it provides the near-optimal performance at low complexity. The MPD significantly outperforms such advanced detector as the semidefinite relaxation detector in both the detection performance and complexity. In MIMO systems, the MPD exhibits more favorable performance/complexity characteristics and can be considered as a promising alternative to the sphere decoder. The matrix inversion is required in many applications. The complexity of matrix inversion is too high and makes its implementation difficult. To overcome the problem, we propose an approach based on the DCD algorithm to simplify the matrix inversion. This approach obtains separately the individual columns of the inverse matrix and costs a very small number of slices, which is suitable for application, e.g. in MIMO-OFDM systems.

Name dc:type.qualificationname

Ph.D

Level dc:type.qualificationlevel

doctoral

Grantor dc:publisher.institution

University of York

Year dc:date.issued

2009

Author dc:creator

• Quan, Zhi

Advisor dc:contributor.advisor

• Zakharov, Yuriy

Identifier

uk.bl.ethos.507569

OAI identifier oai:identifier

oai:etheses.whiterose.ac.uk:1628