Energy-efficient collaborative transmission algorithm based on potential game theory for beamforming

A group of collaborative nodes can efficiently complete spatial long-distance transmission tasks using beamforming technology. However, a high sidelobe level interferes with communication quality, and uneven energy consumption of nodes affects network lifetime. This paper proposes an energy-efficient collaborative transmission algorithm based on potential game theory for beamforming. First, the minimum number of cooperative nodes is determined in accordance with the energy consumption and spacing limitation condition. A group of nodes satisfying the node spacing condition is selected as cooperative nodes based on the ring array to minimize communication interference among nodes. Second, a potential game model is proposed as a joint method for optimizing the collaborative parameters of the cooperative nodes and their energy consumption balancing features. Finally, the game process is continuously executed until the Nash equilibrium is reached. According to simulation results, the sidelobe level caused by the cooperative nodes is reduced and the transmission conflicts are lessened. Thus, the quality of communication links in between nodes in the network is improved. Energy efficiency is also promoted because a balancing of energy consumption is involved in the proposed potential game model, and network lifetime is effectively prolonged accordingly.

[1]  V. Agrawal,et al.  Mutual coupling in phased arrays of randomly spaced antennas , 1972 .

[2]  Nik Noordini Nik Abd Malik,et al.  Circular Collaborative Beamforming for Improved Radiation Beampattern in WSN , 2013, Int. J. Distributed Sens. Networks.

[3]  Chee Yen Leow,et al.  Distributed and Collaborative Beamforming in Wireless Sensor Networks: Classifications, Trends, and Research Directions , 2017, IEEE Communications Surveys & Tutorials.

[4]  Dimitrios Peroulis,et al.  Energy-Efficient Transmission for Beamforming in Wireless Sensor Networks , 2010, 2010 7th Annual IEEE Communications Society Conference on Sensor, Mesh and Ad Hoc Communications and Networks (SECON).

[5]  Fenggan Zhang,et al.  Linear Aperiodic Array Synthesis Using Differential Evolution Algorithm , 2013, IEEE Antennas and Wireless Propagation Letters.

[6]  G. K. Mahanti,et al.  Sidelobe reduction of a scanned and broadside central element fed concentric ring array antenna with fixed first null beamwidth using novel particle swarm optimisation , 2012 .

[7]  Shintaro Mori,et al.  Cooperative sensing data collecting framework by using unmanned aircraft vehicle in wireless sensor network , 2016, 2016 IEEE International Conference on Communications (ICC).

[8]  Mujdat Soyturk,et al.  Analyzing the Effects of UAV Mobility Patterns on Data Collection in Wireless Sensor Networks , 2017, Sensors.

[9]  Kenneth Tze Kin Teo,et al.  Optimization of Distributed and Collaborative Beamforming in Wireless Sensor Networks , 2012, 2012 Fourth International Conference on Computational Intelligence, Communication Systems and Networks.

[10]  Jing Zhang,et al.  Prolonging the lifetime of wireless sensor networks by utilizing feedback control , 2014, Wireless Networks.

[11]  Yinfeng Wu,et al.  Reliable routing in wireless sensor networks based on coalitional game theory , 2016, IET Commun..

[12]  Xu Zhou,et al.  Suppressing Sidelobe Level of the Planar Antenna Array in Wireless Power Transmission , 2019, IEEE Access.

[13]  Hai-gang Gong,et al.  On Prolonging Network Lifetime through Load-Similar Node Deployment in Wireless Sensor Networks , 2011, Sensors.

[14]  Nihad Dib,et al.  Circular antenna array synthesis using firefly algorithm , 2014 .

[15]  Victor C. M. Leung,et al.  Self-Organized Relay Selection for Cooperative Transmission in Vehicular Ad-Hoc Networks , 2017, IEEE Transactions on Vehicular Technology.

[16]  Antonio Barrientos,et al.  An Air-Ground Wireless Sensor Network for Crop Monitoring , 2011, Sensors.

[17]  Raouf Boutaba,et al.  On Balancing Energy Consumption in Wireless Sensor Networks , 2009, IEEE Transactions on Vehicular Technology.

[18]  Quanyuan Feng,et al.  Discrete Optimization Problems of Linear Array Synthesis by Using Real Number Particle Swarm Optimization , 2013 .

[19]  Xiaolin Du,et al.  Planar arrays synthesis for optimal wireless power transmission , 2015, IEICE Electron. Express.

[20]  Kai-Kit Wong,et al.  An Efficient Sensor-Node Selection Algorithm for Sidelobe Control in Collaborative Beamforming , 2016, IEEE Transactions on Vehicular Technology.

[21]  Mianxiong Dong,et al.  UAV-assisted data gathering in wireless sensor networks , 2014, The Journal of Supercomputing.

[22]  Wei Zhang,et al.  Collaborative beamforming for wireless sensor networks with sector-based node selection , 2013, 2013 International Conference on Communications, Circuits and Systems (ICCCAS).

[23]  Shou Qi Cao,et al.  The Application of Wireless Sensor Network in Ocean Fishing Vessel , 2013 .

[24]  Peng Wang,et al.  Collaborative Beamforming for Wireless Sensor Networks with Arbitrary Distributed Sensors , 2012, IEEE Communications Letters.

[25]  Rohit Salgotra,et al.  Synthesis of linear antenna array using flower pollination algorithm , 2016, Neural Computing and Applications.

[26]  Ian F. Akyildiz,et al.  Sensor Networks , 2002, Encyclopedia of GIS.

[27]  Shuguang Cui,et al.  On Design of Collaborative Beamforming for Two-Way Relay Networks , 2011, IEEE Transactions on Signal Processing.

[28]  L. Shapley,et al.  REGULAR ARTICLEPotential Games , 1996 .

[29]  L. Shapley,et al.  Potential Games , 1994 .

[30]  Björn E. Ottersten,et al.  Collaborative-Relay Beamforming With Perfect CSI: Optimum and Distributed Implementation , 2009, IEEE Signal Processing Letters.

[31]  Xu Zhou,et al.  Node selection optimization for collaborative beamforming in wireless sensor networks , 2016, Ad Hoc Networks.

[32]  J. R. Martinez-de Dios,et al.  Cooperation Between UAS and Wireless Sensor Networks for Efficient Data Collection in Large Environments , 2013, J. Intell. Robotic Syst..

[33]  Keyvan Zarifi,et al.  Collaborative Null-Steering Beamforming for Uniformly Distributed Wireless Sensor Networks , 2010, IEEE Transactions on Signal Processing.

[34]  J. N. Sahalos,et al.  A Multi-Objective Approach to Subarrayed Linear Antenna Arrays Design Based on Memetic Differential Evolution , 2013, IEEE Transactions on Antennas and Propagation.

[35]  Rong Du,et al.  Towards Immortal Wireless Sensor Networks by Optimal Energy Beamforming and Data Routing , 2018, IEEE Transactions on Wireless Communications.

[36]  Yutao Ma,et al.  OceanSense: A practical wireless sensor network on the surface of the sea , 2009, 2009 IEEE International Conference on Pervasive Computing and Communications.

[37]  Chee Yen Leow,et al.  PSOGSA-Explore: A new hybrid metaheuristic approach for beampattern optimization in collaborative beamforming , 2015, Appl. Soft Comput..

[38]  Sergiy A. Vorobyov,et al.  Sidelobe Control in Collaborative Beamforming via Node Selection , 2010, IEEE Transactions on Signal Processing.

[39]  Aimin Wang,et al.  A Sidelobe and Energy Optimization Array Node Selection Algorithm for Collaborative Beamforming in Wireless Sensor Networks , 2018, IEEE Access.

[40]  Zhi-qiang Lin,et al.  Sidelobe reduction of the low profile multi-subarray antenna by genetic algorithm , 2012 .