The increasing traffic demand in cellular networks has recently led to the investigation of new strategies to save precious resources like spectrum and energy. A possible solution employs direct device-to-device (D2D) communications, which is particularly promising when the two terminals involved in the communications are located in close proximity. The D2D communications should coexist with other transmissions, so they must be careful scheduled in order to avoid harmful interference impacts. In this paper, we analyze how a distributed context-awareness, obtained by observing few local channel and topology parameters, can be used to adaptively exploit D2D communications. We develop a rigorous theoretical analysis to quantify the balance between the gain offered by a D2D transmission, and its impact on the other network communications. Based on this analysis, we derive two theorems that define the optimal strategy to be employed, in terms of throughput maximization, when a single or multiple transmit power levels are available for the D2D communications. We compare this strategy to the state-of-the-art in the same network scenario, showing how context awareness can be exploited to achieve a higher sum throughput and an improved fairness.
Overall, the main difference between our approach and the existing ones lies in our strategy to mitigate the interference. We do not rely neither on a geographic based criterion, as in @cite_22 , which is easy to implement in a distributed fashion but is static and often over-restrictive, nor on a centralized optimization problem, as in @cite_5 @cite_16 @cite_2 @cite_1 , which achieves optimal solutions, but needs full channel state information over all the involved channels.
@cite_22 @cite_1 @cite_2 @cite_5 @cite_16
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Device-to-device (D2D) communication enables the user equipments (UEs) located in close proximity to bypass the cellular base stations (BSs) and directly connect to each other, and thereby, offload traffic from the cellular infrastructure. D2D communication can improve spatial frequency reuse and energy efficiency in cellular networks. This paper presents a comprehensive and tractable analytical framework for D2D-enabled uplink cellular networks with a flexible mode selection scheme along with truncated channel inversion power control. The developed framework is used to analyze and understand how the underlaying D2D communication affects the cellular network performance. Through comprehensive numerical analysis, we investigate the expected performance gains and provide guidelines for selecting the network parameters. In this paper, we propose using group partition and dynamic rate adaptation for scalable throughput optimization of capacity-region-aware device-to-device communications. We adopt network information theory that allows a receiving device to simultaneously decode multiple packets from multiple transmitting devices, as long as the vector of transmitting rates is inside the capacity region. Based on graph theory, devices are first partitioned into subgroups. To optimize the throughput of a subgroup, instead of directly solving an integer-linear programming problem, we propose using a fast iterative algorithm to select active devices and using aggression levels for rate adaptation based on channel state information. Simulation results show that the proposed algorithm is scalable and could significantly outperform the greedy algorithm by more than 50 . We develop a flexible and accurate framework for device-to-device (D2D) communication in the context of a conventional cellular network, which allows for time-frequency resources to be either shared or orthogonally partitioned between the two networks. Using stochastic geometry, we provide accurate expressions for SINR distributions and average rates, under an assumption of interference randomization via time and or frequency hopping, for both dedicated and shared spectrum approaches. We obtain analytical results in closed or semi-closed form in high SNR regime, that allow us to easily explore the impact of key parameters (e.g., the load and hopping probabilities) on the network performance. In particular, unlike other models, the expressions we obtain are tractable, i.e., they can be efficiently optimized without extensive simulation. Using these, we optimize the hopping probabilities for the D2D links, i.e., how often they should request a time or frequency slot. This can be viewed as an optimized lower bound to other more sophisticated scheduling schemes. We also investigate the optimal resource partitions between D2D and cellular networks when the dedicated spectrum approach is used. Device-to-device (D2D) communications help improve the performance of wireless multicast services in cellular networks via cooperative retransmissions among multicast recipients within a cluster. Resource utilization efficiency should be taken into account in the design of D2D communication systems. To maximize resource efficiency of D2D retransmissions, there is a tradeoff between multichannel diversity and multicast gain. In this paper, by analyzing the relationship between the number of relays and minimal time-frequency resource cost on retransmissions, we derive a closed-form probability density function (pdf) for an optimal number of D2D relays. Motivated by the analysis, we then propose an intracluster D2D retransmission scheme with optimized resource utilization, which can adaptively select the number of cooperative relays performing multicast retransmissions and give an iterative subcluster partition algorithm to enhance retransmission throughput. Exploiting both multichannel diversity and multicast gain, the proposed scheme achieves a significant gain in terms of resource utilization if compared with its counterparts with a fixed number of relays.