Wireless Power Transfer in Distributed Antenna Systems

This paper studies the performance of wireless power transfer in distributed antenna systems (DAS). In particular, the distributed remote radio heads (RRHs), which are conventionally distributed in the network to enhance the performance, are also used to increase the energy harvesting (EH) at the energy-constrained users. Based on this idea, the network area is divided into two zones, namely, A) EH zone and B) Interference zone. The users in the EH zones are guaranteed to harvest sufficient energy from the closed RRH, while the users in the interference zones harvest energy from the surrounding RRHs. A harvest-then-transmit protocol is adopted, where in the power transfer phase the multiple antennas RRHs broadcast energy signals to the users. In the information transmission phase, the users utilize the harvested energy to transmit their signals to the RRHs. In addition, zero-forcing is applied at the RRHs receivers, to mitigate the interference. The system spectral efficiency is evaluated in two different scenarios based on the channel state information (CSI), namely: 1) CSI is unknown at the RRHs; 2) CSI is perfectly known at the RRHs. In contrast to conventional EH-muliple input multiple output (MIMO) systems, performance analysis of EH DAS-MIMO is a challenging problem, because the channels are characterized by non-identical path-loss and EH effects which make the classical analytical methods nontractable. In light of this, new analytical expressions of the ergodic spectral efficiency are derived, and then Monte-Carlo simulations are provided to verify the accuracy of our analysis. The effects of main system parameters on the EH-DAS performance are investigated. The results show that there is an optimal value of the EH time for each users locations that maximizes the system performance. In addition, size of the EH-zone area depends on the required harvested power at the users which is dependent essentially on the target spectral efficiency

How to Increase Energy Efficiency in Cognitive Radio Networks

In this paper, we investigate the achievable energy efficiency of cognitive radio networks where two main modes are of interest, namely, spectrum sharing (known as underlay paradigm) and spectrum sensing (or interweave paradigm). In order to improve the energy efficiency, we formulate a new multiobjective optimization problem that jointly maximizes the ergodic capacity and minimizes the average transmission power of the secondary user network while limiting the average interference power imposed on the primary user receiver. The multiobjective optimization will be solved by first transferring it into a single objective problem (SOP), namely, a power minimization problem, by using the ε-constraint method. The formulated SOP will be solved using two different methods. Specifically, the minimum power allocation at the secondary transmitter in a spectrum sharing fading environment are obtained using the iterative search-based solution and augmented Lagrangian approach for single and multiple secondary links, respectively. The significance of having extra side information and also imperfect side information of cross channels at the secondary transmitter are investigated. The minimum power allocations under perfect and imperfect sensing schemes in interweave cognitive radio networks are also found. Our numerical results provide guidelines for the design of future cognitive radio networks

Energy-Efficient Heterogeneous Cellular Networks with Spectrum Underlay and Overlay Access

In this paper, we provide joint subcarrier assignment and power allocation schemes for quality-of-service (QoS)-constrained energy-efficiency (EE) optimization in the downlink of an orthogonal frequency division multiple access (OFDMA)-based two-tier heterogeneous cellular network (HCN). Considering underlay transmission, where spectrum-efficiency (SE) is fully exploited, the EE solution involves tackling a complex mixed-combinatorial and non-convex optimization problem. With appropriate decomposition of the original problem and leveraging on the quasi-concavity of the EE function, we propose a dual-layer resource allocation approach and provide a complete solution using difference-of-two-concave-functions approximation, successive convex approximation, and gradient-search methods. On the other hand, the inherent inter-tier interference from spectrum underlay access may degrade EE particularly under dense small-cell deployment and large bandwidth utilization. We therefore develop a novel resource allocation approach based on the concepts of spectrum overlay access and resource efficiency (RE) (normalized EE-SE trade-off). Specifically, the optimization procedure is separated in this case such that the macro-cell optimal RE and corresponding bandwidth is first determined, then the EE of small-cells utilizing the remaining spectrum is maximized. Simulation results confirm the theoretical findings and demonstrate that the proposed resource allocation schemes can approach the optimal EE with each strategy being superior under certain system settings

Performance Analysis of Cooperative Diversity in Multi-user Environments

The article studies the performance of cooperative multi-relay networks with random numbers of accessing users. A cooperative diversity is achieved at the destination nodes by receiving multiple independent copies of the same signal from M relays when all relays participate in the second phase of data transmission. The overall spectral efficiency (SE) of the considered system is investigated and accurate analytical expressions for it are developed. Furthermore, the article discusses how system performance is affected by its parameters. Monte Carlo simulations are used to validate the analytical results. The results revealed that increasing relays number on the network can improve the system performance. The results also indicated that there was improvement in the performance when the number of users increased. However, the performance dropped when this number became close the relays number