Design of Detectors and Decoders for MIMO Wireless Systems
Tang, Wei
2019
Abstract
Multiple-Input-Multiple-Output (MIMO) technology makes use of multiple transmit and receive antennas to improve the spectral efficiency and reliability by spatial diversity and multiplexing. However, MIMO systems require complicated baseband detector designs to cancel the Inter-Antenna Interference. This work develops high-performance and energy efficient MIMO detectors using state-of-the-art iterative detection and decoding, message-passing detection and expectation-propagation detection approaches. Iterative Detection and Decoding, or IDD, is an iterative receiver design that improves the error rate performance and relaxes both the detector and decoder designs by iterating the soft decisions between the detector and the decoder. Through iterative interference cancellation and error correction, the Signal-to-Interference-and-Noise Ratio can be substantially improved. We demonstrate a 2.4mm2 4x4 MIMO IDD ASIC incorporating Minimum Mean Squared Error (MMSE) detector and Non-Binary Low-Density Parity Check (NBLDPC) decoder. The IDD chip exploits an nonbinary interface between the detector and the decoder to achieve a 1.02Gb/s throughput, 20pJ/b energy efficiency and superior detector performance compared to previous detector designs. The upcoming 5G wireless communication relies on scaling up the numbers of antennas at the base station, using a new technology known as massive MIMO. Massive MIMO often refers to a multiple-user wireless communication system, where the base station is equipped with hundreds of antennas and serves tens of single-antenna user terminals. A large number of antennas entails a high complexity in baseband digital signal processing. To lower the complexity, previously demonstrated massive MIMO systems deployed linear detectors. Despite its simplicity, a linear detector requires expensive matrix inversion operations, the cost of which can become excessive in a massive MIMO system. In a rich scattering environment, a massive MIMO channel can be modeled as an independently and identically distributed Rayleigh fading channel. This favorable property allows us to explore approximate detection algorithms to greatly reduce the computational complexity while still maintaining close-to-optimal BER-SNR performance. This idea is realized and demonstrated in a 0.58mm2 128x32 low complexity Message-Passing Detector (MPD) for a massive MIMO base station. With a symbol hardening technique, the complexity of the MPD is reduced by more than 60%. The detector is implemented in a pipelined block-parallel architecture using a layered-grouped schedule to accelerate convergence, enabling an average throughput of 2.76Gb/s at 221mW. The chip incorporates adaptive precision control and clock gating to improve energy efficiency to 80pJ/b. Practical massive MIMO channels for mobile applications are fast varying. From the channel measurement by Lund University, it is discovered that the massive MIMO channel could vary and degrade. A highly correlated channel is observed when mobile users are closely deployed in an environment where the line-of-sight signal propagation paths dominate. In such a condition, a conventional MMSE detector is unable to satisfy the BER-SNR requirement. To address this challenge, a 2.0mm2 iterative expectation-propagation detector (EPD) is presented for a 128x16 massive MIMO system supporting up to 256-QAM modulation. Tested with measured channel data, the detector achieves 4.3dB processing gain over state-of-the-art massive MIMO detectors, enabling 2.7 times reduction in transmit power for battery-powered mobile terminals. The EPD chip uses link-adaptive processing to meet a variety of practical channel conditions with scalable energy consumption. The design is realized in a condensed systolic array architecture and an approximate moment-matching circuitry to reach 1.8Gb/s at 70.6pJ/b. The performance and energy efficiency can be tuned over a wide range by the UTBB-FDSOI body bias.Subjects
MIMO detector Massive MIMO iterative detector and decoder (IDD)
Types
Thesis
Metadata
Show full item recordCollections
Remediation of Harmful Language
The University of Michigan Library aims to describe library materials in a way that respects the people and communities who create, use, and are represented in our collections. Report harmful or offensive language in catalog records, finding aids, or elsewhere in our collections anonymously through our metadata feedback form. More information at Remediation of Harmful Language.
Accessibility
If you are unable to use this file in its current format, please select the Contact Us link and we can modify it to make it more accessible to you.