In this paper, we develop a spatiotemporal mathematical model for analyzing the performance of prioritized data transmissions in the device-to-device (D2D) underlaying cellular network. A dynamic interference model of a D2D user is constructed by exploiting thinned Poisson point process to model the D2D user location with data stored in the buffer. A dynamic priority queuing model is adapted to analyze the performance of multiple types of traffic, in which the priority jump strategy is proposed to provide increased transmission opportunity for low-priority user packets. Then, we employ a two-dimensional Geo/G/1 Markov chain to describe a queue model with priority jump and evaluate it using quasi-birth-anddeath process approach. An iterative solution is used to compute the steady-state probability distribution and the expressions of performance metrics are obtained. The simulation results show the validity of the theoretical analysis. Moreover, by comparing the dropping probability of the priority queuing model with and without the jump strategy, the rationality of the introduced model is confirmed. INDEX TERMS Dynamic priority queuing, D2D communication, quasi-birth-and-death (QBD) processes, thinned Poisson point processes (PPP).

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.

Non-orthogonal multiple access (NOMA) technique, which is known to raise the performance of frequency spectrum constrained wireless communication networks, has obtained wide attention. In this paper, a NOMA-based resource allocation problem in the decode-and-forward relaying downlink network is considered. We aim to maximize the average user transmission rate, subject to the total system power constraint and users' quality of service requirement. A joint user-channel assignment and power allocation problem is formulated, which leads to an NP-hard problem requiring an exhaustive search. To tackle this problem, we adopt a decouple optimization method to separate the joint resource problem into two subproblems, a user-channel assignment problem, and a power allocation problem. After solving the two subproblems, a joint alternating optimization algorithm is proposed with low complexity. The simulation results show that the proposed joint optimal scheme can efficiently improve system performance in the limited channels of multiple users relaying networks. INDEX TERMS NOMA, user-channel assignment, power allocation, relay.

We focus on the performance analysis of the buffer-aided relaying system which allows data and energy packets to arrive independently and depart interactively. First, we profile the cooperative relaying system model as a data arrival and energy arrival coupling queuing model. Considering the influence of channel condition on the data departure rate, a new relay transmit protocol which permits exhausting more energy packet to send one data packet in the bad channel environment is proposed. Second, the joint data packet and energy packet handling problem is ascribed to a Coupled Processor Queuing Model which could achieve its steady state transition probability by Quasi-Birth and Death method. Third, the expressions of throughput, delay, and packet drop rate for both data queue and energy queue are also derived. Simulations are demonstrated to verify the analytical results under different data arrival rate, energy arrival rate, and relaying strategy.