In this paper, we propose interference alignment (IA) schemes for downlink multiple-input-multiple-output heterogeneous networks (HetNets) with partial connectivity, which is induced by the path loss and the low transmission power of small cells. Specifically, we consider two partially connected scenarios of HetNets. In the first scenario, we focus on the partial connectivity among small cells, whereas in the second scenario, we further consider the partial connectivity between the macrocell and small cells. For the first scenario, we first propose a two-stage IA scheme by exploiting the heterogeneity and partial connectivity of HetNets. Then, the influence of the number of served macro users on system degrees of freedom (DoFs) is investigated. In particular, we derive the condition under which serving one macro user achieves more DoFs than serving multiple macro users and design an algorithm to find the optimal number of served macro users to maximize the system DoFs. Afterward, we study the second scenario and extend the two-stage IA to this scenario. The simulation results show that the proposed IA schemes can significantly improve the system sum rate. Moreover, by considering the partial connectivity between the macro cell and small cells, the system performance can be further improved.Index Terms-Heterogeneous networks, interference alignment, interference management, partial connectivity.
Energy shortage obstructs the applications of the wireless rechargeable sensor network (WRSN). With the development of the wireless energy transfer technology, the mobile wireless charging vehicle (WCV) becomes a promising solution to solve that problem. However, the importance of different sensor nodes in the data transmission and uneven energy consumptions are often ignored. In this paper, the charging strategy of the WCV is studied in the WRSN considering these two phenomena. According to the importance of the sensor node, which is associated with the distance to the base station, we divide sensor nodes into two types: sensor nodes in ring 0 and sensor nodes in outer ring. We propose a novel charging model, the WCV adopts different charging strategies for different sensor nodes. To make the charging more efficient, the WCV charges sensor nodes one by one in ring 0 first, and then charges multiple sensor nodes simultaneously in outer ring. To estimate the lifetime of the network, a new metric named as the normalized dead time is proposed. Maximizing the lifetime of the network is modeled as minimizing the sum normalized dead time, and an efficient algorithm is proposed to minimize the sum normalized dead time through searching the optimal charging timeslots sequences. Then, through reassigning charging timeslots of sensor nodes, the proposed minimum travel cost algorithm minimizes the travel distance of the WCV and guarantee the lifetime of the network. We further deploy a cluster head node which has larger battery capacity in each cluster and can charge other sensor nodes within a limited distance. An algorithm is proposed to pre-distribute energy of the cluster head node. At last, the performance of proposed algorithms is verified by MATLAB. The results indicate that the performance of the WRSN can be improved by our proposed algorithms. INDEX TERMS Wireless rechargeable sensor network, wireless energy transfer technology, mobile wireless charging vehicle, charging strategy, sum normalized dead time minimization, travel cost minimization.
Recently, wireless energy transfer technology becomes a popular way to address energy shortage in wireless sensor networks. The capacity of the mobile wireless charging car (WCV) and the wireless channel between the WCV and the sensor are two important factors influencing the energy efficiency of the wireless sensor network, which has not been well considered. In this paper, we study the energy efficiency of a wireless rechargeable sensor network charged by a finite capacity WCV through an imperfect wireless channel. To estimate the energy efficiency, we first propose a new metric named waste rate, which is defined as a function of the charging channel quality. Then, energy efficiency optimization is modeled as minimizing the waste rate. Through optimizing the distance between the WCV and sensor nodes, the set of optimal charging sensor nodes is obtained. By using the Hamiltonian circle, the nearest neighbor algorithm is proposed to find the traveling path of the WCV. Furthermore, to avoid the untimely death of sensor nodes and the coverage hole, an extended node dynamic replacement strategy is proposed. The simulation results show that the proposed method can reduce the waste rate and the total charging time; i.e., the sum of traveling time and charging delay can be significantly reduced, which indicates that the proposed algorithm can improve the energy efficiency of the network.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.