Research On Resource Allocation And Relay Selection In OFDMA-based Cognitive Radio Networks

Wireless communications have supported a wide range of high-data-rate applications, becoming part of our everyday lives. The rapid development of wireless technologies has triggered a huge demand for spectrum bandwidth. In consequence of this explosion, frequency spectrum is running out. There is little room to develop new wireless services. Although the static spectrum allocation policy generally served well in the past, under the observation of Federal Communications Commission(FCC), the allocated spectrum remained unutilized at most of time and location. There is a dramatic increase in the access to the scarce spectrum for emerging wireless services and products in the recent years. Cognitive radio is a promising solution to the problem of overcrowded spectrum. It opportunistically exploits the frequency bands licensed to the primary users(PUs) which is not used spatially or temporarily, and utilizes the licensed spectrum to transmit its own data.Since CR network should dynamically allocate unused spectrum among CR users, and be very ?exible to meet the requirements of different services. Orthogonal Frequency Division Multiplexing Access(OFDMA) based cognitive radio has obviously the inherent advantage of allocating radio resource, the analysis of the PU’s activity is easy. Applying CR techniques in OFDMA can alleviate the spectrum shortage crisis, as any idle subchannel can easily be utilized, which is deemed as an air interface for CR systems. The primary system can lease some subchannels to the secondary system for a fraction of time in exchange for the secondary users(SUs) assisting the transmission of primary users(PUs) as relays. Therefore, the performance of both PUs and SUs can be improved, which results a win-win situation. With such cooperation between PUs and SUs, CR system is referred to as cooperative cognitive radio network(CCRN). However, there is a challenging due to the requirement of easy coexistence of both primary and cognitive users. There are lots of issues like, fairness, security threats and energy efficiency that need special consideration. In this dissertation, the resource allocation strategy in CCRN is investigated thoroughly. The author’s major work is outlined as follows:1. To meet the quality of service requirement of multiple users in orthogonal frequency division multiple access wireless network, a low complexity dynamic resource allocation algorithm is proposed. Firstly, the subcarriers are assigned to every user in a rough proportionality. Secondly, the minimum power is allocated to each user according to its rate requirement. Finally, the overall throughput of the system is maximized under the constraint of both the total power and the users’ minimum power. Theoretical analysis and numerical results show the proposed scheme can achieve near-optimum transmit power of user, it can adaptive allocate resource in a short time, which meeting the real-time requirement for wireless communication.2. This dissertation studies the tradeoff between energy efficiency(EE) and spectral efficiency(SE) in cooperative cognitive radio networks, joint power and subcarrier allocation scheme is proposed. Resource is assigned to each user in a way ensures maximizing energy efficiency of primary network, maintaining primary and second user quality of service(QoS) requirements. Optimum transmit power and subcarrier allocation of user are got by analysis, validity of theory is verified by simulation, the proposed algorithm can adaptive allocate resource for CCRN.3. The energy aware resource allocation of multi-user OFDMA cooperative cognitive radio network is investigated. Minimizing energy consumption is one of major design objectives for CCRN, weighted sum power minimization is proposed, subcarriers are assigned to each user in a way that ensures better security level. Everyone is allocated power with Quality of Service(QoS) guarantees, while users’ minimum rate requirements are met. Optimum transmit power of user is obtained by Lagrange method, validity of the low complexity method are verified by simulation. The proposed algorithm can risk-aware allocate resource, minimizing weighted sum of the transmit power.4. The resource allocation problem is investigated for cooperative cognitive radio networks, considering energy efficiency of the primary users(PUs) and spectrum efficiency of the secondary users(SUs). The cooperation framework involves a PU selecting SU as the relay and allocating the spectrum access intervals for the selected SU as a reward. The above sequential decision procedure is formulated as a Stackelberg game. Based on the knowledge of the effects of PUs decision on the behavior of a SU, the leader(PU) determines a fraction of the time slot duration of T is used for the primary. The follower(SU) is allowed to transmit its own data to the corresponding receiver in the remaining duration and determines its optimal transmission power. The outcomes of the proposed cooperative resource allocation scheme, including primary user and secondary user power control, dynamic access spectrum, are analyzed. Numerical results demonstrate that, with the proposed resource allocation scheme, the PU can achieve high energy saving by cooperation with the SU.5. We investigate the effects of channel estimation on dynamic resource allocation for cooperative relay assisted OFDMA radio network. The RRA scheme addresses practical implementation issues of the algorithm: the inaccuracy of channel-state information(CSI) available at the transmitter. Instead, the source only knows estimated channel status based on MMSE channel estimation. The objective is to maximize the system capacity under the optimal amount of power allocated between pilot and data subcarriers. Since the resource optimization problem is known as NP-hard, the original problem is solved by means of a two level dual decomposition and subgradient method. We derive theoretical expressions for the solutions. Moreover, through simulation, results validate coincides the analytical computations. Our proposed resource allocation schemes can enhance the performance of system with imperfect CSI.