Research On Cognitive Network Relay Selection Algorithm

The use of multiple antennas at base stations is the highlight in the design of cellular communications that can meet high-capacity demands in the downlink. Under ideal conditions, the gain of employing multiple antennas is well-recognized: the data throughput increases linearly with the increasing number of transmit antennas when the spatial dimension is utilized to serve many users in parallel. The practical performance of systems is, however, limited by a variety of nonidealities, such as insufficient channel knowledge, transceiver impairments and limited backhaul capacity.The performance of systems depends on the resource allocation strategy; however, inherent conflict lies in resource allocation, such as time, power, frequency, and spatial resources. Allocating proper weights to various factors to develop a suboptimal allocation strategy has triggered significant research activities. Recently, due to the deployment of a variety of wireless devices and the rise of wireless services, spectrum allocation becomes more and more important in the design of allocation policy. Introduction of the beamforming technology can not only improve the spectrum utilization of space effectively, but also limit the interference between users; what’s more, it is able to relieve the pressure caused by the shortage of spectrum to some extent. For different network environments scholars have designed many distinctive beamformer and obtained suboptimal allocation of resources. Obviously, one beamformer can be applied to only one specific environment, and the implementation condition is very strict. With the introduction of new technologies and new methods, the traditional adaptive beamforming technology has been improved rapidly, especially the introduction of convex optimization theory which has contributed significantly to the development of beamforming technology, and attracted widespread attention in recent years. Based on convex optimization theory, domestic and foreign scholars have designed many suboptimal beamformers. Aiming at the non-ideal environments, the beamformers through a variety of methods relax the problem of non-convex optimization to the problem of a convex optimization. It should be noted that robust algorithms represented by the boundary constraint algorithm and probabilistic constraints algorithms aim at a particular environment. The current researches of robust algorithm focus on using different techniques to approximate the values to the optimal value as much as possible.In order to overcome the problem of spectrum shortage, the concept of cognitive relay networks(CRNs) has been put forward. In CRNs, the secondary user(SU) is allowed to access the same spectrum owned by the primary user(PU), and at the same time it should be subject to the constraint that the interference power form the SU to the PU is below a certain threshold. In the process of relay communication, relay nodes share their antennas to create a virtual multiple input and multiple output(MIMO) systems, in order to assist communication between the source node with limited power and the destination node. Through controlling the space allocation of power, beamforming techniques can not only effectively control the interference level but also ensure reliable communication quality.In this article, the author designed a practical and efficient beamformer aiming at real cognitive relay networks environment. Taking into account the differences between the relay environments, the fading characteristics of communication link between the user and relay are different, for example, some links are under deep fading, whereas others are in good conditions. Consequently, not all the relay nodes are suitable for participating relay nodes beamforming. The coexistence of primary users and secondary users makes the design of the relay selection algorithm become difficult. The key of this paper lies in resolving the problem of the spectrum resources shortage and providing reliable communication services by searching for a compromised resource allocation policy between minimum transmission power and the optimal relay subset. Using convex optimization theory, this paper relaxes the more complicated non-convex optimization problem to an easier convex optimization problem to obtain an efficient beamformer.