Abstract
Device-to-device (D2D) communications provide efficient ways to increase spectrum utilization ratio with reduced power consumption for proximity wireless applications. In this paper, we investigate resource allocation strategies for D2D communications underlaying cellular networks. To be specific, we study the centralized resource allocation algorithm for controlling transmit powers of the underlying D2D pairs in order to maximize the weighted sum-rate while guaranteeing the quality of service (QoS) requirements for both D2D pairs and cellular users (CUs). A novel DC (difference of convex function) programming-based method, called alternative DC (ADC) programming, is introduced to effectively solve this complicated resource allocation problem. Through updating each D2D pair’s power alternatively, the QoS requirement for each D2D pair can be solvable and incorporated systematically to the introduced ADC programming framework. The simulation results show that the introduced ADC programming achieves the highest weighted sum-rate compared to the state-of-the-art methods while ensuring that the QoS of each D2D pair and CU are satisfied.
Highlights
To meet the explosively increasing demands of data rate services in mobile networks, device-to-device (D2D) communications attracted a lot of attention from both academia and industry
D2D communications can be deployed in a distributed fashion based on schemes such as spatial spectrum sensing [3], [4] and vehicle-to-vehicle communications [5] to decrease the signaling overhead from the base station (BS) compared to centralized resource allocation algorithms
The results show that the alternative difference of convex functions (DC) (ADC) programming method achieves much better system performance under quality of service (QoS) constraints than the geometric programming (GP) method and existing DC programming methods
Summary
To meet the explosively increasing demands of data rate services in mobile networks, device-to-device (D2D) communications attracted a lot of attention from both academia and industry. We consider a more complicated weighted sum-rate maximization problem for multi-user and multi-channel D2D networks underlaying cellular networks with individual QoS requirements and power constraints. Individual power constraints on D2D pairs are more difficult to solve since they form a more complicated feasible solution set, especially in multi-channel networks Another approach for solving the DC programming problem uses the first-order Taylor series approximation with an iterative method [30], [34], [35]. Main contributions of the paper are as follows: 1) The introduced ADC programming algorithm is able to efficiently solve a complicated weighted sum-rate maximization problem for multi-user and multi-channel D2D networks underlaying cellular networks with individual QoS requirements and power constraints for both D2D pairs and cellular users.
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