Energy-Efficient Management for Cognitive Radio Systems

Abstract

Driven by customers increasing interest in wireless services, resulted in increased demand of radio spectrum. The conventional approach of spectrum management is very inflexible, with major portion of licensed spectrum band already allocated to operator for their spectrum usage. However study of spectrum usage indicated that, the licensed band is rarely utilize continuously across time and space. Furthermore it also has been witnessed that the relatively low utilization of the licensed band suggest that spectrum scarcity, as perceived today, is not because of physical shortage of spectrum but the main reason is due inefficient allocation of licensed band. Cognitive radio is an uprising technique designed to solve the problem of spectrum utilization effectively. The concept of cognitive radio was initially introduced in software defined radio research community, but since than has become its own field of study. A cognitive radio observes its environment and modifies its transmission characteristics accordingly. A cognitive radio uses a cognitive cycle that includes radio spectrum analysis, channel state estimation and predictive modeling and spectrum management. However, the performance of such type of systems can be degraded, due to the factor of non-accurate sensing of the spectrum. Therefore cooperative system for cognitive radios not only increases the accuracy of the decision making but also enhances its reliability. But with cooperation various system evaluation parameters needs to be addressed. This dissertation covers some of the major aspect which are termed as system enhancing parameters of any wireless communication system e.g. throughput and energy consumption analysis. The growing concern regarding environmental issues and emerging green communication paradigm prospective, the cognitive radio system can also be considered from the energy perspective. The quest for efficient system's is primarily because of cost effectiveness, longer battery time and the most important environmental issues. Initial part of the dissertation considers the relation between the control channel power and the data channel power of the cognitive user. Energy should be consumed effectively for cost effective systems. A proposed distance equation with reference to a cognitive radio network constituting of a cognitive base station (CBS), primary transceiver pair and a cognitive user (CU) under the collision probability constraint has been derived and analyzed. Numerical investigation are presented to evaluate the plausible region for transmission of a cognitive user for a targeted data rate using Lame Curve (Chapter 3). In a cooperative cognitive radio system increasing the number of cooperating CU decreases the sensing (detectors) sensitivity and sensing time but the communication over head in terms of message exchange and processing overhead will increase which directly increase the energy consumption of the overall cognitive system. Hence with cooperation also gives rise to many problems, one the biggest problem is the energy consumption. More the number of nodes cooperating, lead to more energy consumption for any system and decreases its energy efficiency (EE). To improve EE in cognitive radio system, letting only a part of CUs be active in sensing and reporting (called a quality-based activation (QBA)) is proposed in latter part of dissertation. Throughput (Chapter 4) and EE (Chapter 5) of cooperative cognitive radio system with the proposed QBA are derived and shown, with numerical investigated in detail. Furthermore in cooperative cognitive radio systems, security establishes another trade-off which affects the cooperation entities due to trust mechanism. Malicious user may propagate false sensing decision to the CBS which severely affect the global decision computed at the CBS. The trade off between throughput and security has been covered (Chapter 6), in order to analyze the attack from malicious users.