Cooperative Spectrum Sharing in Cognitive Radio Networking

Driven by the massive growth in communications data traffic as well as flourishing users' demands, we need to fully utilize the existing scarce spectrum resource. However, there have been several studies and reports over the years showing that a large portion of licensed spectrum is actually underutilized in both temporal and spatial domains. Moreover, aiming at facing the dilemma among the fixed spectrum allocation, the ever enormous increasing traffic demand and the limited spectrum resource, cognitive radio (CR) was proposed by Mitola to alleviate the under usage of spectrum. Thus, cognitive radio networking (CRN) has emerged as a promising paradigm to improve the spectrum efficiency and utilization by allowing secondary users (SUs) to utilize the spectrum hole of primary users (PUs). By using spectrum sensing, SUs can opportunistically access spectrum holes for secondary transmission without interfering the transmissions of the PUs and efficient spectrum utilization by multiple PUs and SUs requires reliable detection of PUs. Nevertheless, sensing errors such as false alarm and misdetection are inevitable in practical networks. Hence, the assumption that SUs always obtain the exact channel availability information is unreasonable. In addition, spectrum sensing must be carried out continuously and the SU must terminate its transmission as soon as it senses the re-occupancy by a PU. As a better alternative of spectrum sensing, cooperation has been leveraged in CRN, which is referred as cooperative cognitive radio networking (CCRN). In CCRN, in order to obtain the transmission opportunities, SUs negotiate with the PUs for accessing the spectrum by providing tangible service for PUs. In this thesis, we study cluster based spectrum sharing mechanism for CCRN and investigate on exploiting the cooperative technique in heterogeneous network. First, we develop cooperation protocols for CRN. Simultaneous transmission can be realized through quadrature signalling method in our proposed cooperation protocol. The optimal power allocation has been analyzed and closed-form solution has been derived for amplify and forward mode. Second, we study a cluster based spectrum sharing mechanism. The spectrum sharing is formulated as a combinatorial non-linear optimization problem which is NP-hard. Afterwards, we solve this problem by decomposing it into cluster allocation and time assignment, and we show that the result is close to the optimal solution. Third, we propose a macrocell-femtocell network cooperation scheme for heterogeneous networks under closed access mode. The cooperation between the femtocell network and macrocell network is investigated. By implementing the cooperation, not only the macrocell users' (MUEs') and femtocell users' (FUEs') utility can be improved compared with the non-cooperation case, but also the energy consumption as well as the interference from the femtocell network to the macrocell network can be reduced

Security-aware Cooperation in Dynamic Spectrum Access

We have witnessed a massive growth in wireless data, which almost doubles every year. The wireless data is expected to skyrocket further in the future due to the proliferation of devices and the emerging data-hungry applications. To accommodate the explosive growth in mobile traffic, a large amount of wireless spectrum is needed. With the limited spectrum resource, the current static spectrum allocation policy cannot serve well for future wireless systems. Moreover, it exacerbates the spectrum scarcity by resulting in severe spectrum underutilization. As a promising solution, dynamic spectrum access (DSA) is envisaged to increase spectrum efficiency by dynamic sharing all the spectrum. DSA can be enabled by cognitive radio technologies, which allow the unlicensed users (the secondary users, i.e., SUs) to dynamically access the unused spectrum (i.e., spectrum holes) owned by the licensed users (the primary users i.e., PUs). In order to identify the unused spectrum (spectrum holes), unlicensed users need to conduct spectrum sensing. While spectrum sensing might be inaccurate due to multipath fading and shadowing. To address this problem, user cooperation can be leveraged, with two main forms: cooperative spectrum sensing and cooperative cognitive radio networking (CCRN). For the former, SUs cooperate with each other in spectrum sensing to better detect the spectrum holes. For the latter, SUs cooperate with the PUs to gain access opportunities from the PUs by improving the transmission performance of the PUs. Whereas cooperation can also incur security issues, e.g., malicious users might participate into cooperation, corrupting or disrupting the communication of legitimate users, selfish users might refuse to contribute to cooperation for self-interests, etc. Those security issues are of great importance and need to be considered for cooperation in DSA. In this thesis, we study security-aware cooperation in DSA. First, we investigate cooperative spectrum sensing in multi-channel scenario such that a user can be scheduled for spectrum sensing and spectrum sharing. The cooperative framework can achieve a higher average throughput per user, which provides the incentive for selfish users to participate in cooperative spectrum sensing. Second, secure communication in CCRN is studied, where the SUs cooperate with the PU to enhance the latter’s communication security and then gain transmission opportunities. Partner selection, spectrum access time allocation, and power allocation are investigated. Third, we study risk aware cooperation based DSA for the multiple channel scenario, where multiple SUs cooperate with multiple PUs for spectrum access opportunities, considering the trustworthiness of SUs. Lastly, we propose an incentive mechanism to stimulate SUs to cooperate with PUs when they have no traffic. The cooperating SUs are motivated to cooperate with PUs to enhance the security of the PUs by accumulating credits and then consume the earned credits for spectrum trading when they have traffic in the future

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