Research On Joint Optimization Scheme Of Multidimensinal Resources For Device-to-Device Communication Underlaying Cellular Network

With the emerging of local applications and smart terminals, close mobile data services are increasing and following by a surge in the consumption of mobile device network traffic, which forcing operators to be faced that mobile communication network should greatly enhance performance, such as terminal energy consumption, cell coverage, spectral and energy efficiency, etc. Then more and more attentions are drew to Device-to-Device (D2D)communication, because a large number of studies have shown that D2D communication as a key technology in the fifth generation systems has potential advantages to adequately address these issues. D2D communication can take advantage of a good channel environment between these devices with short-range communication, allowing adjacent user terminals to be data transmission and information exchange directly by reusing the licensed spectrum of traditional cellular networks, without the relay of base station as a central node. It can not only reduce the load of the base station and improve the spectral efficiency, but also increase the network capacity and expand cell coverage, while reducing terminals’ energy consumption and the communication delay and thus enhance the user experience.However, as a result of spectral sharing, D2D communication underlaying cellular network may impose severe co-channel interference to existing cellular links. Therefore, we need to design a reasonable radio resource allocation scheme to make this interference controlled in order to fully exploit the advantages of D2D communication. To tackle the above issue, this paper mainly designed two radio resource allocation schemes in two different scenarios for D2D links reusing the uplink of cellular network, then to optimize several system target performance. Specific work is divided into two parts:The first part, a joint power control (PC) and channel assignment (CA) was proposed in one single channel corresponding to one single-link scenarios to take full consideration of each overall performance indicator. Optimization objectives involved include five system core performance indicators:the terminal’s total energy consumption, spectral efficiency, energy efficiency, the number of admitted D2D links and the worst individual data rate were optimized, and meanwhile quality-of-service (QoS) requirement incorporating of all links were guaranteed. The scheme is achieved in two steps. Firstly, based on the feasibility testing of a single D2D link, the optimal solution of energy consumption, throughput and energy efficiency and the corresponding optimal transmit power of two links is obtained by PC. Secondly, after the optimization of PC’s feedback information, we continue to solve the CA optimization. For the first four targets, each optimization problem is equivalent to the maximum bipartite graph matching problem, and solved by Hungarian algorithm. For the last target of maximizing the worst data rate, with bottleneck assignment modeling we obtained the final optimal solution of CA by threshold adjustment and augmenting path search algorithm.The second part, our studies are dedicated to the scenario that a sole D2D link is allowed to reuse multiple continuous channels of the LTE-Advance uplink. A joint PC and CA scheme was still proposed to optimize several performance targets of D2D links, which are mainly in three aspects:aggregate throughput, energy consumption and the number of access D2D links, while QoS requirement of cellular links were guaranteed. Specifically, the mechanism can be decomposed into a two-layer structure:the design of lower-layer PC considers the optimal solution of these three optimization targets under any given channel assignment, which turns out to be a convex optimization, and can be perfectly characterized by Karush-Kuhn-Tucker conditions. Based on the above optimum, the design of upper-layer CA belongs to the integer linear programming, which is generally NP-hard. Therefore, a combinatorial auction-based scheme is proposed to achieve the tradeoff between performance and complexity.Thanks to the simulations, the trade-off between different optimization targets is comparatively observed, the efficacy of the proposed joint resource allocation mechanism is verified, and the gain when multiple resource variables are in elaboration is illustrated.