Code-division multiple access (CDMA) technique remains a prominent air-interface technology for personal wireless communication systems. Mobile communication systems based on CDMA is definitely susceptible to multiple access interference (MAI) problem due to the difficulty in maintaining orthogonality of CDMA signals in a mobile environment. MAI which usually limits the machine capacity of the CDMA systems and results in strict power get a grip on requirements to ease the near-far problem could be solved by multiuser detection (MUD) technique through exploiting the info of signals from other interfering users. Meanwhile, MUD and power get a grip on problem would be the root-finding process of solving systems of linear algebraic equations. It is established fact that the iterative method can be used for solving some linear equations corresponding to linear interference cancellation, among MUD structures. In this thesis, the preconditioned iterative symmetric successive overrelaxation (SSOR) method in addition to a new evolutionary computation technique particle swarm optimization (PSO) linear interference cancellation technique are suggested to resolve MAI with simplified computational complexity. Finally, a preconditioned power get a grip on algorithm is introduced for realistic CDMA systems to resolve the near-far problem with drastically fast convergence speed. Simulation results show that the SSOR preconditioner is really a powerful tool for solving the issue of MUD and power get a grip on in CDMA systems and PSO is a good approach for MUD aswell….
Contents: Multiuser detection and power control in CDMA systems
Chapter 1 Introduction
Chapter 2 Implementations Of Mud In Cdma Systems
2.1 Introduction
2.2 System Model
2.3 Ideal Iterations And Particle Swarm Optimization
2.3.1. Iterative Algorithms
2.3.1.1 Iterative Sliding Window Algorithm
2.3.1.2 Ssor Preconditioning Iterative Methods
2.3.1.3 Numerical Results And Discussion
2.3.2 Particle Swarm Optimization
2.3.2.1. Multiuser Cdma System Model
2.3.2.2. Particle Swarm Optimization
2.3.2.3 Simulation Results
2.3.2.4 Conclusion
Chapter 3 Power Control In Cdma Systems Using Preconditioned Iteration Method
3.1 Introduction
3.2 System Model
3.3 Iterative Method
3.3.1 The Dcpc And Csopc Algorithm
3.3.2 Gpbi-Cg Method And Ssor Preconditioning Scheme
3.4 Numerical Results And Discussion
Chapter 4 Conclusions…
Source: City University of Hong Kong