Power Consumption In Wireless Networks Research Articles

Presenting an Optimal Energy-Aware Locating Structure Using the Internet of Things and Device-to-Device Communications on Smartphones

Recently, Device-To-Device (D2D) communications as a novel technology for improving the capacity and reducing power consumption in wireless networks have been taken into account. In D2D communications, multimedia programs utilize a great amount of energy sources and bandwidth to meet the increasing needs of mobile users. To solve the above-mentioned problem, in this paper, a new approach was presented for the localization of D2D communications on smartphones, which was based on the Dynamic Packet Transport and Multimedia Presentation Tracking, protocols as well as the distortion rate. Due to this new approach, the energy-aware optimization space and service quality standards were improved with an evolutionary swarm intelligence algorithm, called the Scaling Optimization Algorithm. Furthermore, 5G technology was used in the current study to speed up internet connections. In this regard, infrastructure was required. Therefore, the Internet of Things as infrastructure was considered in 5G technology. The results of the simulation of the proposed algorithm and its comparison with other algorithms reviewed in this paper hinted at the superiority of this algorithm in reducing energy consumption and improving the service quality standards.

Cognitive radio networks for green wireless communications: an overview

As power consumption results in greenhouse gas emissions and energy costs for operators, analyzing power consumption in wireless networks and portable devices is of crutial importance. Due to environmental effects resulted from energy generation and exploitation as well as the cost of surging energy, energy-aware wireless systems attract unprecedented attention. Cognitive Radio (CR) is one of the optimal solutions that allows for energy savings on both the networks and devices. Thus, cognitive radio contributes to increase spectral and energy efficiency as well as reduction in power consumption. In addition, energy consumption of the CR technologies as intelligent technology should be considered to realize the green networks objective. In this article, we look into energy efficiency of the cognitive wireless network paradigms. Moreover, energy efficiency analysis and modelling in these systems are specifically focused on achieving green communications objectives. However, CRs by altering all elements of wireless data communications are considered in this paper, and the energy-efficient operation and energy efficiency enabler perspectives of CRs are also analyzed.

Base Station Switching and Sleep Mode Optimization With LSTM-Based User Prediction

The base station (BS) switching technique has recently attracted considerable attention for reducing power consumption in wireless networks. In this paper, we propose a novel BS switching and sleep mode optimization method to minimize the power consumption, while ensuring that the arriving user traffic is sufficiently covered. First, the user traffic in multiple time slots was predicted using the long-short term memory (LSTM) prediction model. Subsequently, we solved the Lyapunov optimization problem to obtain the optimal BS switching solution from the trade-off relationship between the reduced power consumption by BS switching and the user traffic handled in time series. Finally, we selected the sleep mode for the switched result by calculating the wake-up time and the power consumption ratio of each sleep mode. Simulation results confirm that the proposed algorithm successfully reduces the total power consumption by approximately 15% while preventing the user data queue from diverging in multiple time slots.

Implementation of envelope detection based Wake-Up Receiver for IEEE 802.15.4 WPAN from off-the-shelf components

Abstract. Power consumption in wireless networks is crucial. In most scenarios the transmission time is short compared to the idle listening time for data transmission, the most power is consumed by the receiver. In low latency systems there is a need for low power wake-up receivers (WuRx) that reduce the power consumption when the node is idle, but keep it responsive. This work presents a WuRx designed out of commercial components to investigate the needs of a WuRx when it is embedded in a Wireless Personal Area Network (WPAN) system in a real environment setup including WLAN and LTE communication and considering interferer rejection. The calculation necessary for the attenuation of those interferers is explained in detail. Furthermore, a system design is presented that fulfills the requirements for this environment and is build from off-the-shelf components.

Reducing Power Consumption of Wireless Networks Through Collaborative DMC Mobile Clusters

Reducing the energy consumption of the wireless networks is significantly important for the economic and ecological sustainability of the ICT industry, as high energy consumption may limit the performance of wireless networks, and is one of the main network costs. To solve the energy consumption problem, especially on the terminal side, a scheme known as distributed mobile cloud (DMC) is considered to be a potential solution. Multiple mobile terminals (MTs) can cooperatively take advantage of good quality links among the MTs to save energy when receiving from the Base Station. In this paper, we aim to find the optimal transmit power to further reduce the energy consumption of DMC. From simulation studies, it is shown that up to 80% energy savings can be accomplished when using optimal transmit power, compared to using the standard DMC without exploring the optimal transmit power.

Energy consumption optimization for green Device-to-Device multimedia communications

Recently, Device-to-Device (D2D) multimedia communications have been envisioned as emerging technology for improving capacity and reducing power consumption in wireless networks. In D2D multimedia communications, multimedia applications consume considerable amount of energy and bandwidth resources to satisfy increasing mobile user demands. To overcome this problem, we have proposed a novel energy consumption optimization method (ECO) for green D2D multimedia communications by using Adaptive Genetic Algorithm. In particular, we first encode the videos by using layered multiple description coding with forward error correction (LMDC-FEC) to protect against error and delays as well as more adaptive to unstable bandwidth in wireless channels. To minimize the average energy consumption by packetizing and transmitting, we then formulate the energy consumption optimization problem and solve it to find out the optimal encoding rate matrix allocated to each video under limited bandwidth resource and high quality constraints. The experimental results demonstrated that our proposed ECO method can achieve remarkable improvements in terms of energy saving, i.e., save up to 64% average energy consumption compared to the other methods, while ensuring high received video quality and satisfying given limited bandwidth.

Outage and energy-efficiency analysis of cognitive radio networks: A stochastic approach to transmit antenna selection

Cognitive radio networks have recently attracted significant research attention owing to their promise for application in future cellular communication. In this light, given the intense power consumption of wireless networks, considerable research is now being directed at designing random cognitive radio networks with enhanced energy efficiency. In this study, we investigate the outage probability and energy efficiency in a cognitive radio network, modeling the locations of the primary users and cognitive users as a Poisson point process. We derive closed-form expressions for the outage probability and energy efficiency with consideration of the probabilities of unoccupied (not utilized by the primary users) channel selection and successful transmission for imperfect detection in an interference-limited environment of cognitive radio network. Furthermore, we propose a transmit antenna selection method for the cognitive transmitter in such networks and accordingly develop closed-form expressions for the outage probability and energy efficiency. The study reported here highlights the importance of combining the capabilities of unoccupied channel selection and successful transmission in cognitive radio networks to achieve optimal performance regarding outage probability and energy efficiency. In terms of energy efficiency, there is an optimal threshold that maximizes the energy efficiency. For implementation in transmit antenna selection, the outage probability can be significantly decreased by increasing the number of transmit antennas, even though the energy efficiency is maximized at the target outage probability.

Enabling Green Wireless Networking With Device-to-Device Links: A Joint Optimization Approach

Device-to-device (D2D) communication has emerged as a promising technique for improving capacity and reducing power consumption in wireless networks. Most existing works on D2D communications either targeted CDMA-based single-channel networks or aimed at maximizing network throughput. In this paper, we, however, aim to enable green D2D communications in OFDMA-based wireless networks. We formally define an optimization problem based on a practical link data rate model, whose objective is to minimize total power consumption while meeting user data rate requirements. We propose solving it using a joint optimization approach by presenting two effective and efficient algorithms, which both jointly determines mode selection, channel allocation and power assignment. It has been shown by extensive simulation results that the proposed algorithms can achieve over 68% power savings, compared to several baseline methods.

A Message-Scheduling Scheme for Energy Conservation in Multimedia Wireless Systems

Reducing power consumption of wireless networks has become a major goal in designing modern multimedia wireless systems. In an effort to reduce power consumption, this paper addresses the issue of scheduling real-time messages in multimedia wireless networks subject to both timing and power constraints. A power-consumption model is introduced to calculate power-consumption rates in accordance with message-transmission rates. Next, a new message-scheduling scheme called Power-aware Real-time Message (PARM) is developed to generate message-transmission schedules that minimize power consumption of multimedia wireless-network interfaces and the probability of missing deadlines for real-time messages. With a power-aware scheduling policy in place, the proposed PARM scheme is very energy-efficient. Experimental results based on a wide variety of synthetic workloads and eight real-world applications show that PARM significantly reduces energy dissipation while maintaining low missed rates. PARM reduces power consumption of data transmissions by up to 99.4% (with an average of 86.7%) for synthetic network traffic and saves energy by up to 60.0% (with an average of 34.1%) in the eight real-world applications.

Regenerative cooperative diversity with path selection and equal power consumption in wireless networks

Recently developed cooperative protocol with distributed path selection provides a simple and practical means of achieving full cooperative diversity in wireless networks. While the best path selection method can significantly improve bit error rate (BER) performance, it may cause unequal power consumption among relay nodes, which may reduce the lifetime of energy-constrained networks. A path selection method under the equal power constraint has been developed for the amplifyand- forward (AF) protocol, but there is no such method for the decode-and-forward (DF) protocol. In this paper, we develop a distributed path selection method with an equal power constraint for the DF protocol. We also analyze the BER performance of our path-selection method. Numerical results demonstrate that the proposed method can guarantee equal power consumption, while achieving full diversity as the best path selection method and providing significant performance gain relative to noncooperative communication.

A practical algorithm for power minimisation in wireless networks by means of multi-hop and load partitioning

We study the problem of minimising the power consumption of wireless networks when the traffic is specified. Initially we consider single-hop networks that model currently existing frequency division multiplex (FDM) and code division multiple access (CDMA) networks and discuss the power minimisation problem for these networks. Next we consider networks where multi-hop transmission is deployed and where a source is allowed to partition its outgoing information flow into several sub-flows each delivered through different multi-hop routes. We present a simple, versatile, suboptimum algorithm for the power minimisation in these Multi-hop, load partitioning (MLP) networks. Finally we carry out a simulation campaign in order to quantify the power savings that are attainable by means of the.proposed algorithm.