Effect of user traffic load on design of energy harvesting cellular base station

Author(s):  
Didem Kivanc Tureli ◽  
Usman Ali
Author(s):  
Kui Xu ◽  
Ming Zhang ◽  
Jie Liu ◽  
Nan Sha ◽  
Wei Xie ◽  
...  

Abstract In this paper, we design the simultaneous wireless information and power transfer (SWIPT) protocol for massive multi-input multi-output (mMIMO) system with non-linear energy-harvesting (EH) terminals. In this system, the base station (BS) serves a set of uplink fixed half-duplex (HD) terminals with non-linear energy harvester. Considering the non-linearity of practical energy-harvesting circuits, we adopt the realistic non-linear EH model rather than the idealistic linear EH model. The proposed SWIPT protocol can be divided into two phases. The first phase is designed for terminals EH and downlink training. A beam domain energy beamforming method is employed for the wireless power transmission. In the second phase, the BS forms the two-layer receive beamformers for the reception of signals transmitted by terminals. In order to improve the spectral efficiency (SE) of the system, the BS transmit power- and time-switching ratios are optimized. Simulation results show the superiority of the proposed beam-domain SWIPT protocol on SE performance compared with the conventional mMIMO SWIPT protocols.


Sensors ◽  
2018 ◽  
Vol 18 (10) ◽  
pp. 3294 ◽  
Author(s):  
Shidang Li ◽  
Chunguo Li ◽  
Weiqiang Tan ◽  
Baofeng Ji ◽  
Luxi Yang

Vehicle to everything (V2X) has been deemed a promising technology due to its potential to achieve traffic safety and efficiency. This paper considers a V2X downlink system with a simultaneous wireless information and power transfer (SWIPT) system where the base station not only conveys data and energy to two types of wireless vehicular receivers, such as one hybrid power-splitting vehicular receiver, and multiple energy vehicular receivers, but also prevents information from being intercepted by the potential eavesdroppers (idle energy vehicular receivers). Both the base station and the energy vehicular receivers are equipped with multiple antennas, whereas the information vehicular receiver is equipped with a single antenna. In particular, the imperfect channel state information (CSI) and the practical nonlinear energy harvesting (EH) model are taken into account. The non-convex optimization problem is formulated to maximize the minimum harvested energy power among the energy vehicular receivers satisfying the lowest harvested energy power threshold at the information vehicular receiver and secure vehicular communication requirements. In light of the intractability of the optimization problem, the semidefinite relaxation (SDR) technique and variable substitutions are applied, and the optimal solution is proven to be tight. A number of results demonstrate that the proposed robust secure beamforming scheme has better performance than other schemes.


Author(s):  
K.N Puniran ◽  
Ahmad Robiah ◽  
Rudzidatul Akmam Dziyauddin

Energy harvesting (EH) module for wireless sensor network has become a promising feature to prolong the conventional battery inside the devices. This emerging technology is gaining interest from sensor manufacturers as well as academicians across the globe. The concept of employing EH module must be cost effective and practical. In such, the use of EH module type besides RF is more realistic due to the size of the scavenger module, the availability of the resources and conversion efficiency. Most of the oil and gas plants have some drawbacks in scavenging RF from surrounding (i.e. router, Wi-Fi, base station, cell phone) due to its placement in remote area and thus limited energy sources could be a threat in this application. Multiple sources, including co-channel interference (CCI) in any constraint nodes is a feasible way of scavenging several wastes from ambient RF energy via wireless mesh topology. In this paper, a 3-node decode-and-forward (DF) model is proposed where the relay node is subject to an energy constraint. Multiple primary sources and CCI are added in the system model known as Multiple-Source and Single-Relay (MSSR). A mathematical model is derived in Time Switching Relaying (TSR) and Power Splitting Relaying (PSR) schemes to obtain an average system throughput at a destination. Numerical simulation with respect to the average throughput and EH ratio was performed and compared with the Single-Source and Single-Relay (SSSR) and ideal receiver. By applying multiple sources and CCI as an energy enhancement at the constraint node, the optimal value of EH ratio for TSR can be reduced significantly by 10% as compared to the ideal receiver whereas the optimal value of EH ratio for PSR is outweigh TSR in terms of overall system throughput.


Author(s):  
Alexandra Bousia ◽  
Elli Kartsakli ◽  
Angelos Antonopoulos ◽  
Luis Alonso ◽  
Christos Verikoukis

Reducing the energy consumption in wireless networks has become a significant challenge, not only because of its great impact on the global energy crisis, but also because it represents a noteworthy cost for telecommunication operators. The Base Stations (BSs), constituting the main component of wireless infrastructure and the major contributor to the energy consumption of mobile cellular networks, are usually designed and planned to serve their customers during peak times. Therefore, they are more than sufficient when the traffic load is low. In this chapter, the authors propose a number of BSs switching off algorithms as an energy efficient solution to the problem of redundancy of network resources. They demonstrate via analysis and by means of simulations that one can achieve reduction in energy consumption when one switches off the unnecessary BSs. In particular, the authors evaluate the energy that can be saved by progressively turning off BSs during the periods when traffic decreases depending on the traffic load variations and the distance between the BS and their associated User Equipments (UEs). In addition, the authors show how to optimize the energy savings of the network by calculating the most energy-efficient combination of switched off and active BSs.


Algorithms ◽  
2019 ◽  
Vol 12 (5) ◽  
pp. 93 ◽  
Author(s):  
Na Su ◽  
Qi Zhu

This paper assumes that multiple device-to-device (D2D) users can reuse the same uplink channel and base station (BS) supplies power to D2D transmitters by means of wireless energy transmission; the optimization problem aims at maximizing the total capacity of D2D users, and proposes a power control and channel allocation algorithm for the energy harvesting D2D communications underlaying the cellular network. This algorithm firstly uses a heuristic dynamic clustering method to cluster D2D users and those in the same cluster can share the same channel. Then, D2D users in the same cluster are modeled as a non-cooperative game, the expressions of D2D users’ transmission power and energy harvesting time are derived by using the Karush–Kuhn–Tucker (KKT) condition, and the optimal transmission power and energy harvesting time are allocated to D2D users by the joint iteration optimization method. Finally, we use the Kuhn–Munkres (KM) algorithm to achieve the optimal matching between D2D clusters and cellular channel to maximize the total capacity of D2D users. Simulation results show that the proposed algorithm can effectively improve the system performance.


2018 ◽  
Vol 17 ◽  
pp. 03015
Author(s):  
Huanhuan MAO ◽  
Pengcheng Zhu ◽  
Jiamin Li

Energy harvesting is one of the promising option for realization of green communication and has been a growing concern recently. In this paper, we address the downlink resource allocation in OFDM system with distributed antennas with hybrid power supply base station, where energy harvesting and non-renewable power sources are used complementarily. A joint subcarrier and power allocation problem is formulated for minimizing the net Energy Consumption Index (ECI) with system Quality of Service (QoS) and bit error rates constraint. The problem is a 0-1 mixed integer nonlinear programming problem due to the binary subcarrier allocation variable. To solve the problem, we design an algorithm based on Lagrange relaxation method and fraction programming which optimizes the power allocation and subcarrier allocation iteratively in two nests. Simulation results show that the proposed algorithm converges in a small number of iterations and can improve net ECI of system greatly.


2019 ◽  
Vol 2019 ◽  
pp. 1-17 ◽  
Author(s):  
Thembelihle Dlamini ◽  
Ángel Fernández Gambín ◽  
Daniele Munaretto ◽  
Michele Rossi

The convergence of communication and computing has led to the emergence of multi-access edge computing (MEC), where computing resources (supported by virtual machines (VMs)) are distributed at the edge of the mobile network (MN), i.e., in base stations (BSs), with the aim of ensuring reliable and ultra-low latency services. Moreover, BSs equipped with energy harvesting (EH) systems can decrease the amount of energy drained from the power grid resulting into energetically self-sufficient MNs. The combination of these paradigms is considered here. Specifically, we propose an online optimization algorithm, called Energy Aware and Adaptive Management (ENAAM), based on foresighted control policies exploiting (short-term) traffic load and harvested energy forecasts, where BSs and VMs are dynamically switched on/off towards energy savings and Quality of Service (QoS) provisioning. Our numerical results reveal that ENAAM achieves energy savings with respect to the case where no energy management is applied, ranging from 57% to 69%. Moreover, the extension of ENAAM within a cluster of BSs provides a further gain ranging from 9% to 16% in energy savings with respect to the optimization performed in isolation for each BS.


Electronics ◽  
2019 ◽  
Vol 8 (2) ◽  
pp. 167 ◽  
Author(s):  
Thanh-Nam Tran ◽  
Miroslav Voznak

Non-Orthogonal Multiple Access (NOMA) is the key technology promised to be applied in next-generation networks in the near future. In this study, we propose a multi-points cooperative relay (MPCR) NOMA model instead of just using a relay as in previous studies. Based on the channel state information (CSI), the base station (BS) selects a closest user equipment (UE) and sends a superposed signal to this UE as a first relay node. We have assumed that there are N UEs in the network and the N-th UE, which is farthest from BS, has the poorest quality signal transmitted from the BS compared the other UEs. The N-th UE received a forwarded signal from N - 1 relaying nodes that are the UEs with better signal quality. At the i-th relaying node, it detects its own symbol by using successive interference cancellation (SIC) and will forward the superimposed signal to the next closest user, namely the ( i + 1 ) -th UE, and include an excess power which will use for energy harvesting (EH) intention at the next UE. By these, the farthest UE in network can be significantly improved. In addition, closed-form expressions of outage probability for users over both the Rayleigh and Nakagami-m fading channels are also presented. Analysis and simulation results performed by Matlab software, which are presented accurately and clearly, show that the effectiveness of our proposed model and this model will be consistent with the multi-access wireless network in the future.


Energies ◽  
2019 ◽  
Vol 12 (12) ◽  
pp. 2336 ◽  
Author(s):  
Chih-Min Yu ◽  
Mohammad Tala’t ◽  
Chun-Hao Chiu ◽  
Chin-Yao Huang

Nowadays, wireless sensor networks (WSNs) are becoming increasingly popular due to the wide variety of applications. The network can be utilized to collect and transmit numerous types of messages to a data sink in a many-to-one fashion. The WSNs usually contain sensors with low communication ability and limited battery power, and the battery replacement is difficult in WSNs for large amount embedded nodes, which indicates a balanced routing strategy is essential to be developed for an extensive operation lifecycle. To realize the goal, the research challenges require not only to minimize the energy consumption in each node but also to balance the whole WSNs traffic load. In this article, a Shortest Path Tree with Energy Balance Routing strategy (SPT-EBR) based on a forward awareness factor is proposed. In SPT-EBR, Two methods are presented including the power consumption and the energy harvesting schemes to select the forwarding node according to the awareness factors of link weight. First, the packet forwarding rate factor is considered in the power consumption scheme to update the link weight for the sensors with higher power consumption and mitigate the traffic load of hotspot nodes to achieve the energy balance network. With the assistance of the power consumption scheme, hotspot nodes can be transferred from the irregular location to the same intra-layer from the sink. Based on this feature, the energy harvesting scheme combines both the packet forwarding rate and the power charging rate factors together to update the link weight with a new battery charging rate factor for hotspot nodes. Finally, simulation results validate that both power consumption and energy harvesting schemes in SPT-EBR achieve better energy balance performance and save more charging power than the conventional shortest path algorithm and thus improve the overall network lifecycle.


Author(s):  
Jaewook Yu ◽  
Woohyung Chun ◽  
Goldie Nejat ◽  
Eric Noel ◽  
K. Wendy Tang

In this paper, the development of affordable self-powered wireless sensor balls is proposed for environmental monitoring. Depending on the area of interest, multiple balls can be either thrown or rolled from a distance into the surrounding area of interest or placed beside the object of interest, and send sensory information back to a central base station, i.e., a laptop, for sensor fusion and processing. In order to achieve fast and robust deployment, reliable data delivery, and smart power management, the paper focuses on the potential wireless network and energy harvesting scheme of the balls. In particular, to support a large number of sensor balls, we show that shortest path routing is essential in minimizing network latency and guarantee timely delivery of critical and emergency information. Furthermore, a vibration-based electromagnetic energy harvesting technique is investigated to capture the energy from the motion of the balls. Experimental results demonstrate the potential development of a network of autonomous self-powered wireless sensor balls.


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