dc.contributor.advisor | Dong, Min | |
dc.contributor.author | Li, Wen | |
dc.date.accessioned | 2016-12-19T20:56:07Z | |
dc.date.accessioned | 2022-03-29T16:48:50Z | |
dc.date.available | 2016-12-19T20:56:07Z | |
dc.date.available | 2022-03-29T16:48:50Z | |
dc.date.issued | 2016-08-01 | |
dc.identifier.uri | https://hdl.handle.net/10155/706 | |
dc.description.abstract | In this thesis, we focus on joint relay beamforming and transceiver processing in multiuser relay network. First of all, we consider the scenario in which multiple source-to-destination (S-D) pairs intend to communicate with the help of multiple distributed
amplify-and-forward (AF) relays. A rank-two beamforming Alamouti scheme is proposed
at the sources and relays, and we aim to minimize maximal individual relay
power subject to pre-defined SINR requirements. The resulting non-convex optimization
problem is solved by ordinary semi-definite relaxation (SDR) and separable SDR
approaches. Compared to conventional rank-one scheme, proposed rank-two methods
provide one more degree of freedom in optimal solution, and have significantly better
performance in terms of min-max per-relay power and optimality gap.
Secondly, we consider the scenario where multiple users exchange information with
each other via a multi-way multi-antenna relaying. Our objective is to jointly design
both relay beamforming and receiver linear processing to maximize the minimum
signal-to-interference-and-noise ratio (SINR) under a relay power budget. The joint
optimization problem is iteratively solved by designing relay beam matrix and receiver
processing matrix. For the latter, both maximum-ratio-combining (MRC) receiver
and zero-forcing (ZF) receiver are designed. The MRC receiver leads to the optimal
iterative design while the ZF receiver has lower computational complexity. We also use
successive interference cancellation (SIC) as our decoding strategy to further enhance
sum-rate. Simulation results show that the proposed iterative algorithm yields higher
achievable sum-rate than the existing partial ZF (PZF) method which uses sum-rate
maximization as the design objective. | en |
dc.description.sponsorship | University of Ontario Institute of Technology | en |
dc.language.iso | en | en |
dc.subject | Peer-to-peer | en |
dc.subject | Multi-way multi-antenna | en |
dc.subject | Relay beamforming | en |
dc.subject | Semidefinite relaxation | en |
dc.title | Joint relay beamforming and transceiver processing in multiuser relay network | en |
dc.type | Thesis | en |
dc.degree.level | Master of Applied Science (MASc) | en |
dc.degree.discipline | Electrical and Computer Engineering | en |