Performance Analysis of DoA Estimation for FDD Cell Free Systems Based on Compressive Sensing Technique

The concept of cell free (CF) massive MIMO systems is a prospective fifth generation communication technology that effort with base stations for the privilege of user-centric coverage. Most studies on the CF massive MIMO system in the past imply that systems that use time division duplexing (TDD), even despite the systems using frequency division duplex (FDD) predominate in today’s wireless communications. When the number of antennas increases in FDD systems, channel state information (CSI) collection and feedback overhead become major issues. In order to mitigate these issues, we make use of the condition that the so-called uplink and downlink multipath components are comparable. Base station takes use of the angle reciprocity may immediately obtain information on channel parameters from the uplink training signal. In this paper, for CF massive MIMO system based on FDD, we provide compressive sensing (CS) of directions of arrival (DoAs) estimation approach of access point cooperation based on the channel parameters. The suggested estimation approach outperforms the established subspace-based technique, according to simulation findings. Additionally, we showed that the results of our compressive sensing estimator against the conventional estimation method. The former demonstrates way far better outcome and performance accordingly than the latter

Resource Allocation in Multi-user MIMO Networks: Interference Management and Cooperative Communications

Nowadays, wireless communications are becoming so tightly integrated in our daily lives, especially with the global spread of laptops, tablets and smartphones. This has paved the way to dramatically increasing wireless network dimensions in terms of subscribers and amount of flowing data. Therefore, the two important fundamental requirements for the future 5G wireless networks are abilities to support high data traffic and exceedingly low latency. A likely candidate to fulfill these requirements is multicell multi-user multi-input multiple-output (MU-MIMO); also termed as coordinated multi-point (CoMP) transmission and reception. To achieve the highest possible performance in MU-MIMO networks, a properly designed resource allocation algorithm is needed. Moreover, with the rapidly growing data traffic, interference has become a major limitation in wireless networks. Interference alignment (IA) has been shown to significantly manage the interference and improve the network performance. However, how practically use IA to mitigate interference in a downlink MU-MIMO network still remains an open problem. In this dissertation, we improve the performance of MU-MIMO networks in terms of spectral efficiency, by designing and developing new beamforming algorithms that can efficiently mitigate the interference and allocate the resources. Then we mathematically analyze the performance improvement of MUMIMO networks employing proposed techniques. Fundamental relationships between network parameters and the network performance is revealed, which provide guidance on the wireless networks design. Finally, system level simulations are conducted to investigate the performance of the proposed strategies