Resource Allocation for Energy-Efficient Device-to-Device Communication in 4G Networks

Device-to-device (D2D) communications as an underlay of a LTE-A (4G) network can reduce the traffic load as well as power consumption in cellular networks by way of utilizing peer-to-peer links for users in proximity of each other. This would enable other cellular users to increment their traffic, and the aggregate traffic for all users can be significantly increased without requiring additional spectrum. However, D2D communications may increase interference to cellular users (CUs) and force CUs to increase their transmit power levels in order to maintain their required quality-of-service (QoS). This paper proposes an energy-efficient resource allocation scheme for D2D communications as an underlay of a fully loaded LTE-A (4G) cellular network. Simulations show that the proposed scheme allocates cellular uplink resources (transmit power and channel) to D2D pairs while maintaining the required QoS for D2D and cellular users and minimizing the total uplink transmit power for all users.Comment: 2014 7th International Symposium on Telecommunications (IST'2014

A Delay-Aware Caching Algorithm for Wireless D2D Caching Networks

Recently, wireless caching techniques have been studied to satisfy lower delay requirements and offload traffic from peak periods. By storing parts of the popular files at the mobile users, users can locate some of their requested files in their own caches or the caches at their neighbors. In the latter case, when a user receives files from its neighbors, device-to-device (D2D) communication is enabled. D2D communication underlaid with cellular networks is also a new paradigm for the upcoming 5G wireless systems. By allowing a pair of adjacent D2D users to communicate directly, D2D communication can achieve higher throughput, better energy efficiency and lower traffic delay. In this work, we propose a very efficient caching algorithm for D2D-enabled cellular networks to minimize the average transmission delay. Instead of searching over all possible solutions, our algorithm finds out the best pairs, which provide the best delay improvement in each loop to form a caching policy with very low transmission delay and high throughput. This algorithm is also extended to address a more general scenario, in which the distributions of fading coefficients and values of system parameters potentially change over time. Via numerical results, the superiority of the proposed algorithm is verified by comparing it with a naive algorithm, in which all users simply cache their favorite files

Radio Resource Allocation for Device-to-Device Underlay Communication Using Hypergraph Theory

Device-to-Device (D2D) communication has been recognized as a promising technique to offload the traffic for the evolved Node B (eNB). However, the D2D transmission as an underlay causes severe interference to both the cellular and other D2D links, which imposes a great technical challenge to radio resource allocation. Conventional graph based resource allocation methods typically consider the interference between two user equipments (UEs), but they cannot model the interference from multiple UEs to completely characterize the interference. In this paper, we study channel allocation using hypergraph theory to coordinate the interference between D2D pairs and cellular UEs, where an arbitrary number of D2D pairs are allowed to share the uplink channels with the cellular UEs. Hypergraph coloring is used to model the cumulative interference from multiple D2D pairs, and thus, eliminate the mutual interference. Simulation results show that the system capacity is significantly improved using the proposed hypergraph method in comparison to the conventional graph based one.Comment: 27 pages,10 figure

Optimal time sharing in underlay cognitive radio systems with RF energy harvesting

Due to the fundamental tradeoffs, achieving spectrum efficiency and energy efficiency are two contending design challenges for the future wireless networks. However, applying radio-frequency (RF) energy harvesting (EH) in a cognitive radio system could potentially circumvent this tradeoff, resulting in a secondary system with limitless power supply and meaningful achievable information rates. This paper proposes an online solution for the optimal time allocation (time sharing) between the EH phase and the information transmission (IT) phase in an underlay cognitive radio system, which harvests the RF energy originating from the primary system. The proposed online solution maximizes the average achievable rate of the cognitive radio system, subject to the $\varepsilon$-percentile protection criteria for the primary system. The optimal time sharing achieves significant gains compared to equal time allocation between the EH and IT phases.Comment: Proceedings of the 2015 IEEE International Conference on Communications (IEEE ICC 2015), 8-12 June 2015, London, U