A Stochastic Geometry Analysis of Energy Harvesting in Large Scale Wireless Networks

In this paper, the theoretical sustainable capacity of wireless networks with radio frequency (RF) energy harvesting is analytically studied. Specifically, we consider a large scale wireless network where base stations (BSs) and low power wireless devices are deployed by homogeneous Poisson point process (PPP) with different spatial densities. Wireless devices exploit the downlink transmissions from the BSs for either information delivery or energy harvesting. Generally, a BS schedules downlink transmission to wireless devices. The scheduled device receives the data information while other devices harvest energy from the downlink signals. The data information can be successfully received by the scheduled device only if the device has sufficient energy for data processing, i.e., the harvested energy is larger than a threshold. Given the densities of BSs and users, we apply stochastic geometry to analyze the expected number of users per cell and the successful information delivery probability of a wireless device, based on which the total network throughput can be derived. It is shown that the maximum network throughput per cell can be achieved under the optimal density of BSs. Extensive simulations validate the analysis.Comment: This paper has been accepted by Greencom 201

Smartphone Camera Based Visible Light Communication

The paper proposes a novel camera-based receiver for visible light communications for a short range mobile-to-mobile communications link. The receiver captures data from the screen of a transmitting smartphone and uses the speeded up robust features algorithm to effectively detect it. The receiver performs a projective transformation to accurately eliminate perspective distortions caused by the displacement of the devices. The paper also introduces a quantization process in order to suppress the inter-symbol interference resulting from the dynamic nature of the environment. A range of experiments are carried out in order to evaluate the system performance when the position parameters are varied. We show that the proposed system is capable of achieving a very high success rate of 98% in recovering the transmitted images under test conditions

Characterization of aggregate received power from power beacons in millimeter wave ad hoc networks

Wireless power transfer (WPT) has emerged as an attractive solution to power future wireless communication networks. In this paper, we consider WPT using power beacons (PBs) for a millimeter wave (mmWave) wireless ad hoc network. Using stochastic geometry, we derive the moment generating function (MGF) and the nth cumulant of the aggregate received power from PBs at a reference receiver in closed-form. The MGF allows the complementary cumulative distribution function (CCDF) of the aggregate received power from PBs to be numerically evaluated. We also compare different closed-form distributions which can be used to approximate the CCDF of the aggregate received power. Our results show that the lognormal distribution provides the best CCDF approximation compared to other distributions considered in the literature. The results also show that under practical setups, it is feasible to power users in a mmWave ad hoc network using PBs.ARC Discovery Projects Grant DP14010113

Optimization of the overall success probability of the energy harvesting cognitive wireless sensor networks

Wireless energy harvesting can improve the performance of cognitive wireless sensor networks (WSNs). This paper considers radio frequency (RF) energy harvesting from transmissions in the primary spectrum for cognitive WSNs. The overall success probability of the energy harvesting cognitive WSN depends on the transmission success probability and energy success probability. Using the tools from stochastic geometry, we show that the overall success probability can be optimized with respect to: 1) transmit power of the sensors; 2) transmit power of the primary transmitters; and 3) spatial density of the primary transmitters. In this context, an optimization algorithm is proposed to maximize the overall success probability of the WSNs. Simulation results show that the overall success probability and the throughput of the WSN can be significantly improved by optimizing the aforementioned three parameters. As RF energy harvesting can also be performed indoors, hence, our solution can be directly applied to the cognitive WSNs that are installed in smart buildings

Wireless Powered Dense Cellular Networks: How Many Small Cells Do We Need?

This paper focuses on wireless powered 5G dense cellular networks, where base station (BS) delivers energy to user equipment (UE) via the microwave radiation in sub-6 GHz or millimeter wave (mmWave) frequency, and UE uses the harvested energy for uplink information transmission. By addressing the impacts of employing different number of antennas and bandwidths at lower and higher frequencies, we evaluate the amount of harvested energy and throughput in such networks. Based on the derived results, we obtain the required small cell density to achieve an expected level of harvested energy or throughput. Also, we obtain that when the ratio of the number of sub-6 GHz BSs to that of the mmWave BSs is lower than a given threshold, UE harvests more energy from a mmWave BS than a sub-6 GHz BS. We find how many mmWave small cells are needed to perform better than the sub-6 GHz small cells from the perspectives of harvested energy and throughput. Our results reveal that the amount of harvested energy from the mmWave tier can be comparable to the sub-6 GHz counterpart in the dense scenarios. For the same tier scale, mmWave tier can achieve higher throughput. Furthermore, the throughput gap between different mmWave frequencies increases with the mmWave BS density.Comment: pages 1-14, accepted by IEEE Journal on Selected Areas in Communication

Wireless Power Transfer in Massive MIMO Aided HetNets with User Association

This paper explores the potential of wireless power transfer (WPT) in massive multiple input multiple output (MIMO) aided heterogeneous networks (HetNets), where massive MIMO is applied in the macrocells, and users aim to harvest as much energy as possible and reduce the uplink path loss for enhancing their information transfer. By addressing the impact of massive MIMO on the user association, we compare and analyze two user association schemes. We adopt the linear maximal ratio transmission beam-forming for massive MIMO power transfer to recharge users. By deriving new statistical properties, we obtain the exact and asymptotic expressions for the average harvested energy. Then we derive the average uplink achievable rate under the harvested energy constraint.Comment: 36 pages, 11 figures, to appear in IEEE Transactions on Communication