Green Communication Based Resource Allocation For OFDMA Network

With the rapidly increasing popularity of intelligent terminals, great convenience has been brought to human life. Meanwhile, due to the broadcast nature of wireless communication systems, problems concerning with security requirements remain a major challenge to enterprise and individual users. Traditionally, most of security work is undertaken on upper layers based on computational complexity. Only in recent years,physical layer approach to achieve security has attracted considerable attention for it quanti?es the measure of secrecy and greatly facilitate cross-layer design. According to information theory, however, secure transmission undesirably antagonizes larger ?ow rate, which is a bottleneck in the course of research. To address this problem, it’s an urgent task for us to design an optimal subcarrier allocation algorithm. Besides, OFDMA is becoming the best candidate for the user interface in the wireless network of next generation because of its high e?ciency on the utilization of frequency spectrum and the high ?exibility on the allocation of resource. At the same time, high-speed transmission of smart terminals increases the transmission power of the base station,which brings about a big challenge for limited supply of resources. In this paper, we are interested in how to utilize renewable green energy and wireless power transfer technical to tackle the increasingly intensifying environmental pollution problems and inadequate resource bottlenecks. Based on the above facts, the objective of this paper is to design cross-layer resource allocation algorithms of OFDMA downlink network to the following three wireless transmission situations:1. Dynamic pricing and hybrid energy management with security requirements. To reduce electricity cost of base station, we equip BS with a hybrid energy supply system consisting of renewable energy and power grid, which operates based onthe observation of time-varying electricity price under real electricity markets and the power demand at the base station. To establish a system-wide revenue,for the network administrator, the algorithm charges each user with dynamic admission fee to fully exploit network resources and carry out congestion control at the same time. Based on the above network model, we design the cross-layer PCHA algorithm and verify its network stability and optimality through rigorous theoretical proof and Matlab simulations.2. Joint optimization of base station and relay power allocation for cooperative OFDMA systems with renewable energy harvesting relay. To improve the provision of high throughput for mobiles at the cell edge that always suffer from bad channel conditions, cooperative OFDMA network model is constructed to solve the problem of equipping cables and greatly reduce power cost. Besides, by the means of dynamic queueing and Lyapunov optimization, we convert the time average maximization problem formulation to a series of instantaneous subproblems. The proposed algorithm, RCNA, investigates the joint problem of power allocation and subcarrier assignment with relay selection at the same time. Finally, we prove our algorithm can guarantee network stability and obtain performance extremely close to the optimal by adjusting control parameter V, which is also proved by simulation results.3. Wireless power transmission based BS mode selection, delay control and resource allocation. To handle the problem of outdoor renewable resource unavailable to indoor mobiles and improve frequency e?ciency under low data requests,we extend BS operation mode to wireless power transmission mode. However,secure transmission based wireless power transmission mode may bring about relatively high transmission delay. Thus, we construct virtual delay queue and propose a novel Lyapunov function to design cross-layer DFRA algorithm: in the case that the random data request to BS is relatively low and users’ delay demand is loose or mobile terminals’ battery power is inadequate, BS will transmit power to users through radio frequency.Speci?cally, DFRA transfers data buffer pressure from actual data queue of network layer to the virtual queue of transmission layer, which means there existstradeoff between network throughput and delay bound. What’s more, the actual data queue has speci?c and instantaneous bound, which is independent of control parameter V, that is to say, actual data queue length won’t be increased when performance extremely closes to the optimal.