Power and Rate Optimization in Shared-Spectrum Wireless Communication Networks
type: CreativeWork
description: The growth of wireless applications and the emerging technologies require more efficient management of frequency spectrum. Adaptive resource allocation (i.e. transmission power and transmission rate) and opportunistic spectrum sharing are two key techniques with enormous potential to enhance the efficient utilization of the precious bandwidth and optimizing the performance. Adaptive algorithms are a vital feature of radio resource management (RRM) in third generation (3G) communication systems, and cognitive radio (CR) is a valuable technique with tremendous potential for improving the utilization of the radio spectrum. On the other hand, transition from the current 3G cellular communications systems to the fourth generation (4G) would happen gradually and take several years. During this period, both 3G and 4G technologies are expected to co-exist, and the aforementioned CR technology and adaptation techniques are suitable candidates to be used by service providers for achieving higher data rates in the future heterogeneous networks. In this thesis, novel adaptive transmission algorithms will be developed for shared-spectrum CR networks in the context of direct-sequence code division multiple access (DS-CDMA). This thesis makes several contributions. First, adaptive transmission is integrated into spectrum sharing problem. The joint optimization of power and rate is investigated, where optimality is in the sense of maximizing the average spectral efficiency of the reference cognitive user (CU). A close-form solution for the optimal outer loop power control target signal-to-noise ratio (SNR-target) of the reference CU is derived. The optimization is conducted when the reference CU is using interference-limited opportunistic spectrum access (IL-OSA) technique for utilizing the primary spectrum simultaneously with the primary users. The proposed optimization algorithm's performance is analyzed for a case, wherein the reference CU exploits the licensed spectrum subject …
abstract: The growth of wireless applications and the emerging technologies require more efficient management of frequency spectrum. Adaptive resource allocation (i.e. transmission power and transmission rate) and opportunistic spectrum sharing are two key techniques with enormous potential to enhance the efficient utilization of the precious bandwidth and optimizing the performance. Adaptive algorithms are a vital feature of radio resource management (RRM) in third generation (3G) communication systems, and cognitive radio (CR) is a valuable technique with tremendous potential for improving the utilization of the radio spectrum. On the other hand, transition from the current 3G cellular communications systems to the fourth generation (4G) would happen gradually and take several years. During this period, both 3G and 4G technologies are expected to co-exist, and the aforementioned CR technology and adaptation techniques are suitable candidates to be used by service providers for achieving higher data rates in the future heterogeneous networks. In this thesis, novel adaptive transmission algorithms will be developed for shared-spectrum CR networks in the context of direct-sequence code division multiple access (DS-CDMA). This thesis makes several contributions. First, adaptive transmission is integrated into spectrum sharing problem. The joint optimization of power and rate is investigated, where optimality is in the sense of maximizing the average spectral efficiency of the reference cognitive user (CU). A close-form solution for the optimal outer loop power control target signal-to-noise ratio (SNR-target) of the reference CU is derived. The optimization is conducted when the reference CU is using interference-limited opportunistic spectrum access (IL-OSA) technique for utilizing the primary spectrum simultaneously with the primary users. The proposed optimization algorithm's performance is analyzed for a case, wherein the reference CU exploits the licensed spectrum subject …
author: Mirtavoosi Mahyari, Mohammad
language: eng
date published: 2013-7-1
date modified: 2026-07-24T02:44:40Z
provider: King's College London
publisher: Networked Digital Library of Theses and Dissertations
type: WebPage
source organization: King's College London