Drone assisted device to device cooperative communication for critical environments

Abstract

This paper proposes drone assisted device-to-device cooperative communication (DA-DDCC) for critical situations during post-disaster management. The proposed network utilizes the autonomous mode of D2D communication for setting up the link in the absence of a central node. This network incorporates cooperative communication using drone in D2D session for improving reliability of the overall system. A probability-based statistical channel model for such networks is proposed by taking the statistical independence of links into consideration. Unlike the existing air-to-ground (A2G) channel models that use either Rayleigh or Rician distribution for uplink (UL) and downlink (DL) channel modelling, our approach takes the probability of occurrence of line of sight (LoS) into account while predicting the appropriate channel distribution for UL and DL separately. For performance evaluation of the proposed network, average outage probability and average capacity are derived using the proposed channel model. Monte Carlo simulations are conducted to verify our analysis. Moreover, a multi-cluster DA-DDCC scenario is also being analyzed through simulations from an interference perspective to justify the usefulness of the proposed channel model. Results obtained through this investigation can be utilized in selecting various crucial system parameters judiciously for enhanced performance during post-disaster scenario. 1 INTRODUCTION In recent years, fifth-generation (5G) and beyond 5G (B5G) technologies are being developed to increase the data rates and network capacity for conventional cellular networks. Multiple input multiple output (MIMO) and network traffic offloading techniques are used for achieving such objectives [1-3]. Equipping multiple antennas needs more hardware, cost, and size. Consequently, these methods are not preferred for most of the battery operated tiny devices. To enhance the cellular network performance, traffic offloading techniques are also used in literature. Traffic offloading may be achieved mainly by two methods, one is through small cell (micro/pico/femto) deployment in macro-cells and the other is using device-to-device (D2D) communications [4]. However, the first method may be inconvenient due to a lack of dynamism that occurs because of This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.

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