Energy Efficiency Strategy in D2D Cognitive Networks Using Channel Selection Based on Game Theory and Collaboration

Abstract

The growth of Device-to-Device (D2D) communications and the extensive use of Wireless Sensor Networks (WSNs) bring new problems such as spectral coexistence and spectrum saturation. Cognitive Radio (CR) appears as a paradigm to solve these problems. The introduction of CR into WSNs as a solution to the spectrum utilization problem could be used not only to increase the reliability of communications, but also to optimize energy consumption. The contribution of this paper is a cognitive lightweight strategy based on game theory and collaboration proposed to save energy consumption in Cognitive Wireless Sensor Networks (CWSNs). The proposed strategy takes advantage of the two main capabilities of CWSNs, the ability to adapt communication parameters, specifically channel allocation, and collaboration among devices. The decision making is modeled through a light noncooperative game designed for low resources networks. Despite the fact that the game used is a noncooperative game, the decision process takes advantage of the collaboration among CWSN nodes in a distributed way. Simulations over Castalia Simulator have been carried out in order to validate the strategy in different scenarios with different interference schemes showing increases in energy savings around 50% depending on the scenario.

Distributed beamforming algorithm based on game theory in device-to-device communications

“…Game theory provides a mathematical tool to solve the problem of resource competition and cooperation. 27–32 In general, cooperative games require frequent exchange of information between game participants, which results in huge information overhead and poor scalability in large networks; non-cooperative game is an effective tool to formulate a distributed algorithm, but the non-cooperative game’s Nash equilibrium point is generally worse than the optimization center algorithm. On the other hand, price strategy is another effective way to overcome the inefficiency of non-cooperative game.…”

Caching deployment based on energy efficiency in device-to-device cooperative networks

“…Recently, the demand for video delivery services has dramatically increased, which promotes the exponential growth of wireless data traffic. [1][2][3] However, conventional solutions like the ultra-dense network with increased base station (BS) deployment density, the millimeter-wave communication using higher frequency spectrum communication, and the multiple input multiple output (MIMO) technology cost too much and have reached their limits. 4 Thus, new paradigms need to be studied to enhance the performance of traditional cellular network architecture.…”

“…The optimal caching policy algorithmStep1: Initialize q to a feasible value.Repeat {Loop}:Step2: Update y by equation(2).…”

Cross-layer strategies for improving the quality of service of wireless sensor networks

“…In them, sensing information from neighboring nodes is used by each node to better identify the less crowded channel [38]. Collaborative game-theory schemes can also be used for this purpose, effectively reducing the energy consumption of each node [39].…”

“…It was designed by Javier Blesa and Elena Romero in the context of their Ph.D. theses, carried out at B105 Electronic Systems Lab under the supervision of Alvaro Araujo. The static routing module was then utilized as part of the strategy proposed in the work in [39] and is featured in its corresponding simulations.…”