Research On The Key Technologies Of Cognitive Radio And Caching Networks

In recent years, with the development of mobile terminals and the emergence of vari-ous content-centric software, the mobile traffic has experienced an explosive growth. The enormous traffic raises new challenges of spectrum resource and network architecture. To deal with the exponential growth of the mobile data demand, we consider two promising techniques. The first one is the cognitive radio, which enhances the spectrum utilization efficiency by spectrum sharing. The second one is the content caching, which is able to shorten the distance between contents and users and improve network performance.Although the cognitive radio has been widely studied around the world, there also exist some key issues to be solved. Besides, the research on the content caching is still in the initial stage and is far from mutuality. To accelerate the applications of both cognitive radio and content caching in practice, we investigate several key issues of both techniques.The contributions and novelties are list as follows:1)In the overlay cognitive network, cognitive users adopt spectrum sensing to learn whether a incumbent frequency band is or is not occupied by incumbent users, and de-termine whether to transmit the cognitive data or not. We consider imperfect spectrum sensing and study the impacts of spectrum sensing duration and cognitive transmit power on the energy efficiency of the cognitive network. In particular, we propose two joint op-timization algorithm to maximize the energy efficiency of the cognitive network, theoret-ically analyze their computational complexities, and show both advantages and disadvan-tages of each algorithm. Finally, we validate the proposed algorithms through simulation results.2)In the underlay cognitive network, cognitive users are allowed to use the incum-bent frequency bands even if these frequency bands are occupied. This enhances the spectrum efficiency compared with the overlay cognitive network. Nevertheless, cogni-tive users have to manage the interference to incumbent users. Thus, the cross-channel gain from a cognitive transmitter to a incumbent receiver is crucial for the cognitive trans-mitter. We propose a proactive cross-channel gain estimation algorithm, and obtain the cross-channel gain with a closed-from expression. Meanwhile, we take the impact of additive Gaussian white noise into consideration and derive the upper bound and lower bound of the estimator. In addition, we design the position of the cognitive transmitter and optimize the CT's impact on the primary transmission. Finally, we verify the proposed estimation through simulation results.3)In a Device-to-Device (D2D) aided wireless caching network, if the requested content of a specific has been pre-stored in the local storage, the use can direct access the content. If the requested content has been pre-stored in the storage of nearby users,the user can obtain the requested content through D2D transmissions. If the requested content is neither pre-stored in the local storage nor the storage of nearby users, the user requests the content from the BS or server. In this network, we numerically optimize the distributed content placement scheme, propose a heuristic D2D link scheduling algorithm together with the optimal power allocation algorithm. Simulation results indicate that,the proposed algorithms can efficiently utilize the storage capacity of each node in the network, offload the traffic of the BS or the server, and enhance D2D transmissions.4)In a practical wireless network, the network topology is usually hierarchical and each node in the network has a storage capacity. The optimal caching scheme in this network is still an open problem. Thus, we study a two-layer network and study the optimal caching scheme. In particular, we propose a novel two-layer caching scheme,strictly analyze the performance limit. By comparing with the existing caching scheme in a two-layer caching network, we demonstrate the advantages of the proposed scheme.