Stackelberg Game for Wireless Powered and Backscattering Enabled Sensor Networks

This paper investigates a wireless powered and backscattering enabled sensor network based on the non-linear energy harvesting model, where the power beacon(PB) delivers energy signals to wireless sensors to enable their passive backscattering and active transmission to the access point(AP). We propose an efficient time scheduling scheme for network performance enhancement, based on which each sensor can always harvest energy from the PB over the entire block except its time slots allocated for passive and active information delivery. Considering the PB and wireless sensors are from two selfish service providers, we use the Stackelberg game to model the energy interaction among them. To address the non-convexity of the leader-level problem, we propose to decompose the original problem into two subproblems and solve them iteratively in an alternating manner. Specifically, the successive convex approximation, semi-definite relaxation(SDR) and variable substitution techniques are applied to find a nearoptimal solution. To evaluate the performance loss caused by the interaction between two providers, we further investigate the social welfare maximization problem. Numerical results demonstrate that compared to the benchmark schemes, the proposed scheme can achieve up to 35.4% and 38.7% utility gain for the leader and the follower, respectively.

Resource Allocation for IRS Assistedmm Wave Wireless Powered Sensor Networks with User Cooperation

In this paper,we investigate IRS-aided user cooperation(UC)scheme in millimeter wave(mmWave)wirelesspowered sensor networks(WPSN),where two single-antenna users are wireless powered in the wireless energy transfer(WET)phase first and then cooperatively transmit information to a hybrid access point(AP)in the wireless information transmission(WIT)phase,following which the IRS is deployed to enhance the system performance of theWET andWIT.We maximized the weighted sum-rate problem by jointly optimizing the transmit time slots,power allocations,and the phase shifts of the IRS.Due to the non-convexity of the original problem,a semidefinite programming relaxation-based approach is proposed to convert the formulated problem to a convex optimization framework,which can obtain the optimal global solution.Simulation results demonstrate that the weighted sum throughput of the proposed UC scheme outperforms the non-UC scheme whether equipped with IRS or not.

Experimental Analysis of Link Estimation Methods in Low Power Wireless Networks

Wireless sensor networks are envisioned to be an integral part of cyber-physical systems, yet wireless networks are inherently dynamic and come with various uncertainties. One such uncertainty is wireless communication itself which assumes complex spatial and temporal dynamics. For dependable and predictable performance, therefore, link estimation has become a basic element of wireless network routing. Several approaches using broadcast beacons and/or unicast MAC feedback have been proposed in the past years, but there is still no systematic characterization of the drawbacks and sources of errors in bea- con-based link estimation in low-power wireless networks, which leads to ad hoc usage of beacons in rout- ing. Using a testbed of 98 XSM motes （an enhanced version of MICA2 motes）, we characterize the negative impact that link layer retransmission and traffic-induced interference have on the accuracy of beacon-based link estimation, and we show that data-driven link estimation and routing achieve higher event reliability （e.g. by up to 18.75%） and transmission efficiency （e.g., by up to a factor of 1.96） than beacon-based approaches These findings provide solid evidence for the necessity of data-driven link estimation and demonstrate the importance of addressing the drawbacks of beacon-based link estimation when designing protocols for low-power wireless networks of cyber-physical systems.

Combined spatial-temporal energy harvesting and relay selection for cognitive wireless powered networks

In order to improve the Energy Efficiency(EE)and spectrum utilization of Cognitive Wireless Powered Networks(CWPNs),a combined spatial-temporal Energy Harvesting(EH)and relay selection scheme is proposed.In the proposed scheme,for protecting the Primary User(PU),a two-layer guard zone is set outside the PU based on the outage probability threshold of the PU.Moreover,to increase the energy of the CWPNs,the EH zone in the two-layer guard zone allows the Secondary Users(SUs)to spatially harvest energy from the Radio Frequency(RF)signals of temporally active PUs.To improve the utilization of the PU spectrum,the guard zone outside the EH zone allows for the constrained power transmission of SUs.Moreover,the relay selection transmission is designed in the transmission zone of the SU to improve the EE of the CWPNs.In addition to the EE of the CWPNs,the outage probabilities of the SU and PU are derived.The results reveal that the setting of a two-layer guard zone can effectively reduce the outage probability of the PU and improve the EE of CWPNs.Furthermore,the relay selection transmission decreases the outage probabilities of the SUs.

POWER CONTROL BASED COOPERATIVE OPPORTUNISTIC ROUTING IN WIRELESS SENSOR NETWORKS

This paper proposes an approach called PC-CORP (Power Control based Cooperative Opportunistic Routing Protocol) for WSN (Wireless Sensor Networks), providing robustness to the random variations in network connectivity while ensuring better data forwarding efficiency in an energy efficient manner. Based on the realistic radio model, we combine the region-based routing, rendezvous scheme, sleep discipline and cooperative communication together to model data forwarding by cross layer design in WSN. At the same time, a lightweight transmission power control algorithm called PC-AIMD (Power Control Additive Increase Multiplicative Decrease) is introduced to utilize the co- operation of relay nodes to improve the forwarding efficiency performance and increase the robustness of the routing protocol. In the simulation, the performance of PC-COPR is investigated in terms of the adaptation of variations in network connectivity and satisfying the QoS requirements of application.

Distributed power control algorithm based on game theory for wireless sensor networks

Energy saving is the most important issue in research and development for wireless sensor networks. A power control mechanism can reduce the power consumption of the whole network. Because the character of wireless sensor networks is restrictive energy, this paper proposes a distributed power control algorithm based on game theory for wireless sensor networks which objects of which are reducing power consumption and decreasing overhead and increasing network lifetime. The game theory and OPNET simulation shows that the power control algorithm converges to a Nash Equilibrium when decisions are updated according to a better response dynamic.

Joint Predictive Control of Power and Rate for Wireless Networks

为了在分布式的无线网络，预兆的力量和率控制计划减轻循环延期，为系统模型被建议也说明拥挤层次和输入延期而不是在一个网络推迟状态。有输入延期的一个测量反馈控制问题被最小化之间的差别的精力提出实际并且控制的需要的 signal-to-interference-plus-noise 比率(SNR ) 层次，以及精力定序。解决这个问题，我们在场为控制的二个 Riccati 方程和在时间的评价推迟系统。一个完全的分析最佳的控制器被使用分离原则并且解决二个 Riccati 方程获得，在一个人是为随机的线性二次的规定的向后的方程，其它是标准过滤 Riccati 方程的地方。模拟结果说明建议力量和率控制计划的表演。

Power control and channel allocation optimization game algorithm with low energy consumption for wireless sensor network

In a wireless sensor network （WSN）, the energy of nodes is limited and cannot be charged. Hence, it is necessary to reduce energy consumption. Both the transmission power of nodes and the interference among nodes influence energy consumption. In this paper, we design a power control and channel allocation game model with low energy consumption （PCCAGM）. This model contains transmission power, node interference, and residual energy. Besides, the interaction between power and channel is considered. The Nash equilibrium has been proved to exist. Based on this model, a power control and channel allocation optimization algorithm with low energy consumption （PCCAA） is proposed. Theoretical analysis shows that PCCAA can converge to the Pareto Optimal. Simulation results demonstrate that this algorithm can reduce transmission power and interference effectively. Therefore, this algorithm can reduce energy consumption and prolong the network lifetime.

Power Line Monitoring Data Transmission Using Wireless Sensor Network

The WSN used in power line monitoring is long chain structure, and the bottleneck near the Sink node is more obvious. In view of this, A Sink nodes’ cooperation mechanism is presented. The Sink nodes from different WSNs are adjacently deployed. Adopting multimode and spatial multiplexing network technology, the network is constructed into multi-mode-level to achieve different levels of data streaming. The network loads are shunted and the network resources are rationally utilized. Through the multi-sink nodes cooperation, the bottlenecks at the Sink node and its near several jump nodes are solved and process the competition of communication between nodes by channel adjustment. Finally, the paper analyzed the method and provided simulation experiment results. Simulation results show that the method can solve the funnel effect of the sink node, and get a good QoS.

A Novel Practical Cooperative Diversity Method for the Power-Limited Wireless Sensor Network

A novel practical cooperative diversity method for power-limited wireless sensor network system was proposed. At first, the system model was presented and the cooperation problem is formulated under the minimum outage probability criterion, then the focus was put on the power efficiency of system, such as the relay selection, cooperation strategy and power allocation etc. At last the uniform procedure of the proposed method was given. The results of the simulation clearly demonstrate that our method not only has the properties of simple operation and wide applying scope, but also outperforms those of current classical methods on the aspect of outage probability under the basis of the same power limitation.

Low Power Transceiver Design Parameters for Wireless Sensor Networks

Designing low power sensor networks has been the general goal of design engineers, scientist and end users. It is desired to have a wireless sensor network (WSN) that will run on little power (if possible, none at all) thereby saving cost, and the inconveniences of having to replace batteries in some difficult to access areas of usage. Previous researches on WSN energy models have focused less on the aggregate transceiver energy consumption models as compared to studies on other components of the node, hence a large portion of energy in a WSN still get depleted through data transmission. By studying the energy consumption map of the transceiver of a WSN node in different states and within state transitions, we propose in this paper the energy consumption model of the transceiver unit of a typical sensor node and the transceiver design parameters that significantly influences this energy consumption. The contribution of this paper is an innovative energy consumption model based on simple finite automata which reveals the relationship between the aggregate energy consumption and important power parameters that characterize the energy consumption map of the transceiver in a WSN;an ideal tool to design low power WSN.

POWER CONTROL STRATEGIES FOR MULTICHANNEL COGNITIVE WIRELESS NETWORKS WITH OPPORTUNISTIC INTERFERENCE CANCELLATION

In this letter,an Opportunistic Interference Cancellation(OIC) is first introduced as a rate control strategy for secondary user in cognitive wireless networks. Based on the OIC rate control method,an optimal power control strategy for multichannel cognitive wireless networks is proposed. The algorithm aims to maximize the total transmit rate of cognitive user through appropriately controlling the transmit power of each subchannel under the constraint that the interference temperature at the primary receiver is below a certain threshold. Three suboptimal power control methods,namely Equal Power Transmission(EPT) ,Equal Rate Transmission(ERT) and Equal Interference Transmission(EIT) ,are also proposed. The performances of the proposed power control methods are compared through numerical simulations.

A Power Graded Data Gathering Mechanism for Wireless Sensor Networks

The data gathering manner of wireless sensor networks, in which data is forwarded towards the sink node, would cause the nodes near the sink node to transmit more data than those far from it. Most data gathering mechanisms nowdo not do well in balancing the energy consumption among nodes with different distances to the sink, thus they can hardly avoid the problem that nodes near the sink consume energy more quickly, which may cause the network rupture from the sink node. This paper presents a data gathering mechanism called PODA, which grades the output power of nodes according to their distances from the sink node. PODA balances energy consumption by setting the nodes near the sink with lower output power and the nodes far from the sink with higher output power. Simulation results show that the PODA mechanism can achieve even energy consumption in the entire network, improve energy efficiency and prolong the network lifetime.

Mid-Range Wireless Power Transfer and Its Application to Body Sensor Networks

It has been reported that, through the evanescent near fields, the strongly coupled magnetic resonance is able to achieve an efficient mid-range Wireless Power Transfer (WPT) beyond the characteristic size of the resonator. Recent studies on of the relay effect of the WPT allow more distant and flexible energy transmission. These new developments hold a promise to construct a fully wireless Body Sensor Network (wBSN) using the new mid-range WPT theory. In this paper, a general optimization strategy for a WPT network is presented by analysis and simulation using the coupled mode theory. Based on the results of theoretical and computational study, two types of thin-film resonators are designed and prototyped for the construction of wBSNs. These resonators and associated electronic components can be integrated into a WPT platform to permit wireless power delivery to multiple wearable sensors and medical implants on the surface and within the human body. Our experiments have demonstrated the feasibility of the WPT approach.

Local adaptive transmit power assignment strategy for wireless sensor networks

A distributed local adaptive transmit power assignment (LA-TPA) strategy was proposed to construct a topology with better performance according to the environment and application scenario and prolong the network lifetime.It takes the path loss exponent and the energy control coefficient into consideration with the aim to accentuate the minimum covering district of each node more accurately and precisely according to various network application scenarios.Besides,a self-healing scheme that enhances the robustness of the network was provided.It makes the topology tolerate more dead nodes than existing algorithms.Simulation was done under OMNeT++ platform and the results show that the LA-TPA strategy is more effective in constructing a well-performance network topology based on various application scenarios and can prolong the network lifetime significantly.

A Novel Low-Complexity Low-Latency Power Efficient Collision Detection Algorithm for Wireless Sensor Networks

Collision detection mechanisms in Wireless Sensor Networks (WSNs) have largely been revolving around direct demodulation and decoding of received packets and deciding on a collision based on some form of a frame error detection mechanism, such as a CRC check. The obvious drawback of full detection of a received packet is the need to expend a significant amount of energy and processing complexity in order to fully decode a packet, only to discover the packet is illegible due to a collision. In this paper, we propose a suite of novel, yet simple and power-efficient algorithms to detect a collision without the need for full-decoding of the received packet. Our novel algorithms aim at detecting collision through fast examination of the signal statistics of a short snippet of the received packet via a relatively small number of computations over a small number of received IQ samples. Hence, the proposed algorithms operate directly at the output of the receiver's analog-to-digital converter and eliminate the need to pass the signal through the entire. In addition, we present a complexity and power-saving comparison between our novel algorithms and conventional full-decoding (for select coding schemes) to demonstrate the significant power and complexity saving advantage of our algorithms.

Adaptive ant-based routing in wireless sensor networks using Energy~* Delay metrics

To find the optimal routing is always an important topic in wireless sensor networks (WSNs). Considering a WSN where the nodes have limited energy, we propose a novel Energy*Delay model based on ant algorithms ("E&D ANTS" for short) to minimize the time delay in transferring a fixed number of data packets in an energy-constrained manner in one round. Our goal is not only to maximize the lifetime of the network but also to provide real-time data transmission services. However, because of the tradeoff of energy and delay in wireless network systems, the reinforcement learning (RL) algorithm is introduced to train the model. In this survey, the paradigm of E&D ANTS is explicated and compared to other ant-based routing algorithms like AntNet and AntChain about the issues of routing information, routing overhead and adaptation. Simulation results show that our method performs about seven times better than AntNet and also outperforms AntChain by more than 150% in terms of energy cost and delay per round.

A Game Theoretic Approach for Inter-Network Interference Mitigation in Wireless Body Area Networks

Wireless Body Area Network(WBAN) is an emerging technology to provide real-time health monitoring and ubiquitous healthcare services. In many applications, multiple wireless body area networks have to coexist in a small area, resulting in serious inter-network interference. This not only reduces network reliability that is especially important in emergency medical applications, but also consumes more power of WBANs. In this paper, an inter-network interference mitigation approach based on a power control algorithm is proposed. Power control is modeled as a non-cooperative game, in which both inter-network interference and energy efficiency of WBANs are considered. The existence and uniqueness of Nash Equilibrium in the game are proved, and an optimal scheme based on best response is proposed to find its Nash Equilibrium. By coordinating the transmission power levels among networks under interference environment, the total system throughput can be increased with minimum power consumed. The effectiveness of the proposed method has been illustrated by simulation results, where the performance of the proposed approach is evaluated in terms of overall utility and power efficiency and convergence speed.

Heterogeneous Quality of Experience Guarantees Over Wireless Networks

Quality of experience(Qo E), which is very critical for the experience of users in wireless networks, has been extensively studied. However, due to different human perceptions, quantifying the effective capacity of wireless network subject to diverse Qo E is very difficult, which leads to many new challenges regarding Qo E guarantees in wireless networks. In this paper, we formulate the Qo E guarantees model for cellular wireless networks. Based on the model, we convert the effective capacity maximization problem into the equivalent convex optimization problem. Then, we develop the optimal Qo E-driven power allocation scheme, which can maximize the effective capacity. The obtained simulation results verified our proposed power allocation scheme, showing that the effective capacity can be significantly increased compared with that of traditional Qo E guarantees based schemes.

Power Splitting Based SWIPT in Network-Coded Two-Way Networks with Data Rate Fairness:An Information-Theoretic Perspective

This paper investigates the simultaneous wireless information and powertransfer(SWIPT) for network-coded two-way relay network from an information-theoretic perspective, where two sources exchange information via an SWIPT-aware energy harvesting(EH) relay. We present a power splitting(PS)-based two-way relaying(PS-TWR) protocol by employing the PS receiver architecture. To explore the system sum rate limit with data rate fairness, an optimization problem under total power constraint is formulated. Then, some explicit solutions are derived for the problem. Numerical results show that due to the path loss effect on energy transfer, with the same total available power, PS-TWR losses some system performance compared with traditional non-EH two-way relaying, where at relatively low and relatively high signalto-noise ratio(SNR), the performance loss is relatively small. Another observation is that, in relatively high SNR regime, PS-TWR outperforms time switching-based two-way relaying(TS-TWR) while in relatively low SNR regime TS-TWR outperforms PS-TWR. It is also shown that with individual available power at the two sources, PS-TWR outperforms TS-TWR in both relatively low and high SNR regimes.