Studies on efficient spectrum sharing in coexisting wireless networks.

Wireless communication is facing serious challenges worldwide: the severe spectrum shortage along with the explosive increase of the wireless communication demands. Moreover, different communication networks may coexist in the same geographical area. By allowing multiple communication networks cooperatively or opportunistically sharing the same frequency will potentially enhance the spectrum efficiency. This dissertation aims to investigate important spectrum sharing schemes for coexisting networks. For coexisting networks operating in interweave cognitive radio mode, most existing works focus on the secondary network’s spectrum sensing and accessing schemes. However, the primary network can be selfish and tends to use up all the frequency resource. In this dissertation, a novel optimization scheme is proposed to let primary network maximally release unnecessary frequency resource for secondary networks. The optimization problems are formulated for both uplink and downlink orthogonal frequency-division multiple access (OFDMA)-based primary networks, and near optimal algorithms are proposed as well. For coexisting networks in the underlay cognitive radio mode, this work focuses on the resource allocation in distributed secondary networks as long as the primary network’s rate constraint can be met. Global optimal multicarrier discrete distributed (MCDD) algorithm and suboptimal Gibbs sampler based Lagrangian algorithm (GSLA) are proposed to solve the problem distributively. Regarding to the dirty paper coding (DPC)-based system where multiple networks share the common transmitter, this dissertation focuses on its fundamental performance analysis from information theoretic point of view. Time division multiple access (TDMA) as an orthogonal frequency sharing scheme is also investigated for comparison purpose. Specifically, the delay sensitive quality of service (QoS) requirements are incorporated by considering effective capacity in fast fading and outage capacity in slow fading. The performance metrics in low signal to noise ratio (SNR) regime and high SNR regime are obtained in closed forms followed by the detailed performance analysis

Opportunity Detection for OFDMA-Based Cognitive Radio Systems with Timing Misalignment

Abstract-Accurate detection of spectrum opportunities within the frequency band of an orthogonal frequency division multiple access (OFDMA) system carries critical importance for OFDMAbased cognitive radios. In this paper, we analyze the opportunity detection performances of energy detection and ESPRIT (estimation of signal parameters by rotational invariance techniques) algorithms in the presence of timing misalignments in uplink (UL) OFDMA. For the energy detector, the statistics of subcarrier power are derived considering timing misalignments, and they are verified through computer simulations. Using these statistics, which take inter-carrier-interference (ICI) effects into account, receiver operating characteristics (ROCs) of the energy detector receiver are obtained. It is shown that energy detection has a considerably better performance than ESPRIT, especially when the subcarrier assignment changes frequently. Moreover, a closed form expression is derived for the UL-OFDMA synchronization point that minimizes the ICI. Finally, it is shown that employing resource allocation blocks with larger sizes in the primary network yields better opportunities for the cognitive radio

Spectrum sharing systems for improving spectral efficiency in cognitive cellular network

Since spectrum is the invisible infrastructure that powers the wireless communication, the demand has been exceptionally increasing in recent years after the implementation of 4G and immense data requirements of 5G due to the applications, such as Internet-of-Things (IoT). Therefore, the effective optimization of the use of spectrum is immediately needed than ever before. The spectrum sensing is the prerequisite for optimal resource allocation in cognitive radio networks (CRN). Therefore, the spectrum sensing in wireless system with lower latency requirements is proposed first. In such systems with high spatial density of the base stations and users/objects, spectrum sharing enables spectrum reuse across very small regions. The proposed method in this Thesis is a multi-channel cooperative spectrum sensing technique, in which an independent network of sensors, namely, spectrum monitoring network, detects the spectrum availability. The locally aggregated decision in each zone associated with the zone aggregator (ZA) location is then passed to a decision fusion centre (DFC). The secondary base station (SBS) accordingly allocates the available channels to secondary users to maximize the spectral efficiency. The function of the DFC is formulated as an optimization problem with the objective of maximizing the spectral efficiency. The optimal detection threshold is obtained for different cases with various spatial densities of ZAs and SBSs. It is further shown that the proposed method reduces the spectrum sensing latency and results in a higher spectrum efficiency. Furthermore, a novel power allocation scheme for multicell CRN is proposed where the subchannel power allocation is performed by incorporating network-wide primary system communication activity. A collaborative subchannel monitoring scheme is proposed to evaluate the aggregated subchannel activity index (ASAI) to indicate the activity levels of primary users. Two utility functions are then defined to characterize the spectral efficiency (SE) and energy efficiency (EE) as a function of ASAI to formulate a utility maximization problem. The optimal transmit power allocation is then obtained with the objective of maximizing the total utility at the SBS, subject to maximum SBS transmit power and collision probability constraint at the primary receivers. Since optimal EE and SE are two contradicting objectives to obtain the transmit power allocation, the design approach to handle both EE and SE as a function of common network parameter, i.e., ASAI, is provided which ultimately proves the quantitative insights on efficient system design. Extensive simulation results confirm the analytical results and indicate a significant improvement in sensing latency and accuracy and a significant gain against the benchmark models on the rate performance, despite the proposed methods perform with lower signalling overhead

Spectrum sharing systems for improving spectral efficiency in cognitive cellular network

Since spectrum is the invisible infrastructure that powers the wireless communication, the demand has been exceptionally increasing in recent years after the implementation of 4G and immense data requirements of 5G due to the applications, such as Internet-of-Things (IoT). Therefore, the effective optimization of the use of spectrum is immediately needed than ever before. The spectrum sensing is the prerequisite for optimal resource allocation in cognitive radio networks (CRN). Therefore, the spectrum sensing in wireless system with lower latency requirements is proposed first. In such systems with high spatial density of the base stations and users/objects, spectrum sharing enables spectrum reuse across very small regions. The proposed method in this Thesis is a multi-channel cooperative spectrum sensing technique, in which an independent network of sensors, namely, spectrum monitoring network, detects the spectrum availability. The locally aggregated decision in each zone associated with the zone aggregator (ZA) location is then passed to a decision fusion centre (DFC). The secondary base station (SBS) accordingly allocates the available channels to secondary users to maximize the spectral efficiency. The function of the DFC is formulated as an optimization problem with the objective of maximizing the spectral efficiency. The optimal detection threshold is obtained for different cases with various spatial densities of ZAs and SBSs. It is further shown that the proposed method reduces the spectrum sensing latency and results in a higher spectrum efficiency. Furthermore, a novel power allocation scheme for multicell CRN is proposed where the subchannel power allocation is performed by incorporating network-wide primary system communication activity. A collaborative subchannel monitoring scheme is proposed to evaluate the aggregated subchannel activity index (ASAI) to indicate the activity levels of primary users. Two utility functions are then defined to characterize the spectral efficiency (SE) and energy efficiency (EE) as a function of ASAI to formulate a utility maximization problem. The optimal transmit power allocation is then obtained with the objective of maximizing the total utility at the SBS, subject to maximum SBS transmit power and collision probability constraint at the primary receivers. Since optimal EE and SE are two contradicting objectives to obtain the transmit power allocation, the design approach to handle both EE and SE as a function of common network parameter, i.e., ASAI, is provided which ultimately proves the quantitative insights on efficient system design. Extensive simulation results confirm the analytical results and indicate a significant improvement in sensing latency and accuracy and a significant gain against the benchmark models on the rate performance, despite the proposed methods perform with lower signalling overhead