Algorithms and VLSI architectures for detection in massive MIMO systems for 5G

• Κύριος συγγραφέας: Κομποστιώτης, Δημήτριος
• Άλλοι συγγραφείς: Kompostiotis, Dimitrios
• Γλώσσα: English
• Έκδοση: 2021
• Θέματα: 5G; BER; MIMO; FPGA; MMSE; Fast Fourier transform; Expectation propagation; Base station; Κεραίες μετάδοσης; Δίκτυα 5G; Επικοινωνία άνω ζεύξης

The increasing demand for higher data rates and for more connected devices has led to the adoption of Massive MIMO Technologies for transmission in wireless channels. Having a high number of transmit and receive antennas is the basic feature of Massive MIMO networks and this is what differentiates them from conventional MIMO systems where users communicate using base stations with a small number of antennas. Massive MIMO technology has many benefits such as high link reliability, high throughput rate, high spectral efficiency and therefore it plays a crucial role at 5G networks. However due to the large number of antennas, Massive MIMO systems are known for their cost and for their high computational complexity. The complexity of optimum detectors such as MAP and ML increases fast with the number of antennas, which makes their implementation and application in networks practically impossible. Expectation Propagation (EP) algorithm provides a good bit error rate (BER) performance similar to linear algorithms when ≫ , where linear algorithms behave as the optimals. Also, EP seems to maintain this good behavior with low BERs compared to linear detectors, even when the number of transmission antennas is about the same as the number of receiving antennas. Moreover, the complexity of EP algorithm is polynomial in contrast with the complexity of MAP and ML detectors complexity, which rises exponentially with the number of transmit and receive antennas. EP is an iterative algorithm that attempts to minimize the Kullback Leibler divergence and approach the probability density function used for the MAP criterion via Gaussian distributions. Specifically, in the iterative section, an attempt is made to approximate the average value of the distribution, that we are interested in, because the average, or otherwise, the expected value of the distribution will be the estimate for the symbol that was sent. In this thesis, an implementation of an EP in a Massive MIMO network is presented. This thesis focuses on uplink communication where users transmit data to the base station. Furthermore a comparison between EP and other detectors, proposed in the literature, is presented based on BER performance using MATLAB simulations. Various methods of calculating the inverse of a matrix are used in this thesis considering the computational complexity, the latency and the required word length for hardware implementation. Implementation results of these methods are also evaluated. Finally, some hardware implementations of EP targeting FPGA designs are recommended.