Secure Resource Allocation Framework for Device-to-Device Communication

Abstract

The exponential rise in the use of numerous data-hungry applications, such as live video streaming, augmented reality, virtual reality, and live conferences, generates massive network traffic, which degrades the overall network’s spectral efficiency. To meet the data requirements of the aforementioned data-hungry applications with quality of service (QoS), the existing cellular infrastructure needs up-gradation, which is highly expensive. So, to improve spectral efficiency, researchers proposed a novel device-to-device (D2D) communication technology. The primary aim of D2D communication is to increase the network’s spectral efficiency by allowing user devices to communicate directly without depending upon the centralized base station (BS). D2D communication offloads the network data traffic to reduce the burden on BS, considering either overlay or underlay mode. In overlay mode, a dedicated spectrum is allocated to the D2D user (DU), whereas in underlay mode. The DU re-utilizes the cellular user’s (CLU’s) spectrum. However, the underlay mode degrades the performance of the D2D communication system (DCS), which is due to severe interference between DUs and CLUs. It includes mutual interference from CLUs-DUs, DUs-CLUs, and between DUs if they utilize the same spectral resource. Mitigating interference in an underlay DCS is a challenging issue that needs to be managed appropriately. Also, the existing underlay DCS infrastructure depends on the orthogonal multiple access (OMA) scheme for spectral reuse, where one resource block (RB) can serve only one user. Thus, OMA degrades the overall spectral efficiency of the DCS and supports limited connections, making the overall D2D communication expensive. This issue can be resolved by involving power domain non-orthogonal multiple access (NOMA) in DCS, where one RB can be served among multiple users with varying power levels based on their channel conditions. In NOMA, the receiver receives a superimposed signal, and the successive interference cancellation (SIC) technique helps segregate user information. However, NOMA improves the spectral efficiency, but can cause NOMA interference, i.e., inter-user interference. Thus, there is a need for an effective and efficient resource allocation (RA) and interference management scheme for the DCS. In addition to interference, the DCS is not robust against eavesdropping and non-trusted DUs due to direct links between proximity devices. Thus, a secrecy-ensured RA scheme is also required to help minimize eavesdropping by satisfying the QoS requirements of CLUs and DUs. Also, there is a requirement to improvise the signal-to-interference-plus-noise ratio (SINR) of edge DUs, leading in improvising the overall performance of the DCS. In this research work, we propose various schemes to mitigate the aforementioned issues in DCS: Firstly, we propose a novel network selection scheme for DUs located at the cell edge in a multi-cell scenario to improve the DCS’s overall sum rate (SR). Initially, we use an AI algorithm to classify BSs as 0 (bad) or 1 (good) based on their respective reference signal received power (RSRP) channel indicator values. The AI algorithm filter out N best BS among M available BSs in a multi-cell scenario. Then, we apply a cell selection algorithm for a particular DU that takes N best BSs as input and select one best BS among them. The second scheme is ”AI and channel indicator-based access control mechanism for D2D communication”. In this, firstly, we apply the AI-based Fisher Jenks natural break (FJNB) optimization algorithm and kernel density estimation clustering (KDEC) to analyze the behavior of DUs in the DCS. This scheme restricts DUs from accessing the spectral resource, which are in the malicious or potential eavesdropper category. Lastly, for secure RA and interference mitigation in DCS, we propose two different schemes considering coalition game and zero-sum game theories. For the first scheme, we propose a joint cognitive radio (CR) and coalition game-based RA scheme for DUs in the DCS. It improves the overall SR and SC of the DCS by integrating NOMA over the traditional OMA scheme. Furthermore, the proposed scheme allows D2D users to change their initial coalitions based on channel conditions to improve their individual DR and SC values. For the second scheme, we utilize a zero-sum game theory to maximize the overall SR and SC of the DCS in the presence of eavesdroppers and non-trusted DUs. To simulate the aforementioned schemes, MATLAB 2022a has been used and for parameter settings, we consider the 3GPP urban path loss model (Release- 15).