Performance Analysis of D2D Communication with Retransmission Mechanism in Cellular Networks

Abstract

In this paper, we focus on the performance analysis of device-to-device (D2D) underlay communication in cellular networks. First, we develop a spatiotemporal traffic model to model a retransmission mechanism for D2D underlay communication. The D2D users in backlogged statuses are modeled as a thinned Poisson point process (PPP). To capture the characteristics of sporadic wireless data generation and limited buffer, we adopt queuing theory to analyze the performance of dynamic traffic. Furthermore, a feedback queuing model is adopted to analyze the performance with retransmission strategy. With the consideration of interference and channel fading, the service probability of the queue departure process is determined by the received signal-to-interference-plus-noise ratio (SINR). Then, the embedded Markov chain is employed to depict the queuing status in the D2D user buffer. We compute its steady-state distribution and derive the closed-form expressions of performance metrics, namely the average queue length, average throughput, average delay, and dropping probability. Simulation results show the validity and rationality of the theoretical analysis with different channel parameters and D2D densities. In addition, the simulation explores the dropping probability of a D2D user with and without the retransmission strategy for different D2D links in the system. When the arrival rate is comparatively high, the optimal throughput is reached after fewer retransmission attempts as a result of the limited buffer.

On the Performance of Underlay Device-to-Device Communications

“…In particular, their proposed scheme, which was suitable for any infrastructure, was significantly enhanced the security of any D2D settings. The works in [12][13][14] applied tools from stochastic geometry (SG) in order to better capture the randomness of both the D2D and the cellular users. More specifically, the closed-form expressions of average queue length, average throughput, average delay, and dropping probability were evaluated in [12].…”

“…The works in [12][13][14] applied tools from stochastic geometry (SG) in order to better capture the randomness of both the D2D and the cellular users. More specifically, the closed-form expressions of average queue length, average throughput, average delay, and dropping probability were evaluated in [12]. On the other hand, authors in [13] derived coverage probability (Pcov) of the cellular users.…”

Adaptive relay selection based on channel gain and link distance for cooperative out-band device-to-device networks

“…Based on the approach to the transmission phase of cooperative communication systems, SNR is calculated in two ways: the first is based on the effect of distance between S → relay → D [27], and the second is based on the impact of fading [28]. Based on the effect of the distance between S to N-relay, the SNR calculation is as follows:…”

“…The adaptive method is proposed for the cooperative out-band D2D communication system with a multi-relay network model. The simulation results of ARS schemes will also be compared to those of existing relay selection schemes: maximum channel gain [27] and minimum distance [28] schemes by using the QF cooperative protocol.…”

Machine Learning Based User Retention and Channel Allocation: 6G Aspect

“…Various texts have been reported for queuing analysis of wireless 5G network. An M/M/1 queue with service interruption from primary users was measured and an evaluating policy was used to charge each secondary user that arrives on a queue [13][14]. Reference [15] suggested a queuing model for optimum resource allocation to achieve a greater overall capacity based on user category.…”