Device-to-device communication in cellular networks : multi-hop path selection and performance.

Over the past decade, the proliferation of internet equipment and an increasing number of people moving into cities have significantly influenced mobile data demand density and intensity. To accommodate the increasing demands, the fifth generation (5G) wireless systems standards emerged in 2014. Device-to-device communications (D2D) is one of the three primary technologies to address the key performance indicators of the 5G network. D2D communications enable devices to communicate data information directly with each other without access to a fixed wireless infrastructure. The potential advantages of D2D communications include throughput enhancement, device energy saving and coverage expansion. The economic attraction to mobile operators is that significant capacity and coverage gains can be achieved without having to invest in network-side hardware upgrades or new cell deployments. However, there are technical challenges related to D2D and conventional cellular communication (CC) in co-existence, especially their mutual interference due to spectrum sharing. A novel interference-aware-routing for multi-hop D2D is introduced for reducing the mutual interference. The first verification scenario of interference-aware-routing is that in a real urban environment. D2D is used for relaying data across the urban terrain, in the presence of CC communications. Different wireless routing algorithms are considered, namely: shortest-path-routing, interference-aware-routing, and broadcast-routing. In general, the interference-aware-routing achieves a better performance of reliability and there is a fundamental trade-off between D2D and CC outage performances, due to their mutual interference relationship. Then an analytical stochastic geometry framework is developed to compare the performance of shortest-path-routing and interference-aware-routing. Based on the results, the spatial operational envelopes for different D2D routing algorithms and CC transmissions based on the user equipment (UEs) physical locations are defined. There is a forbidden area of D2D because of the interference from the base stations (BSs), so the collision probability of the D2D multi-hop path hitting the defined D2D forbidden area is analysed. Depend on the result of the collision probability, a dynamic switching strategy between D2D and CC communications in order to minimise mutual interference is proposed. A blind gradient-based transmission switching strategy is developed to avoid collision within the collision area and only requires knowledge of the distances to the serving base station of the current user and the final destination user. In the final part of my research, the concept of LTE-U (Long term evolution for Unlicensed Spectrum), which suggests that LTE can operate in the unlicensed spectrum with significant modifications to its transmission protocols, is investigated. How the envisaged D2D networks can efficiently scale their capacity by utilising the unlicensed spectrum with appropriately designed LTE-Unlicensed protocols is examined

Radio Link Enabler for Context-aware D2D Communication in Reuse Mode

Device-to-Device (D2D) communication is considered as one of the key technologies for the fifth generation wireless communication system (5G) due to certain benefits provided, e.g. traffic offload and low end-to-end latency. A D2D link can reuse resource of a cellular user for its own transmission, while mutual interference in between these two links is introduced. In this paper, we propose a smart radio resource management (RRM) algorithm which enables D2D communication to reuse cellular resource, by taking into account of context information. Besides, signaling schemes with high efficiency are also given in this work to enable the proposed RRM algorithm. Simulation results demonstrate the performance improvement of the proposed scheme in terms of the overall cell capacity

Distributed Interference-Aware Energy-Efficient Resource Allocation for Device-to-Device Communications Underlaying Cellular Networks

The introduction of device-to-device (D2D) into cellular networks poses many new challenges in the resource allocation design due to the co-channel interference caused by spectrum reuse and limited battery life of user equipments (UEs). In this paper, we propose a distributed interference-aware energy-efficient resource allocation algorithm to maximize each UE's energy efficiency (EE) subject to its specific quality of service (QoS) and maximum transmission power constraints. We model the resource allocation problem as a noncooperative game, in which each player is self-interested and wants to maximize its own EE. The formulated EE maximization problem is a non-convex problem and is transformed into a convex optimization problem by exploiting the properties of the nonlinear fractional programming. An iterative optimization algorithm is proposed and verified through computer simulations.Comment: 6 pages, 3 figures, IEEE GLOBECOM 201

A Game-Theoretic Approach to Energy-Efficient Resource Allocation in Device-to-Device Underlay Communications

Despite the numerous benefits brought by Device-to-Device (D2D) communications, the introduction of D2D into cellular networks poses many new challenges in the resource allocation design due to the co-channel interference caused by spectrum reuse and limited battery life of User Equipments (UEs). Most of the previous studies mainly focus on how to maximize the Spectral Efficiency (SE) and ignore the energy consumption of UEs. In this paper, we study how to maximize each UE's Energy Efficiency (EE) in an interference-limited environment subject to its specific Quality of Service (QoS) and maximum transmission power constraints. We model the resource allocation problem as a noncooperative game, in which each player is self-interested and wants to maximize its own EE. A distributed interference-aware energy-efficient resource allocation algorithm is proposed by exploiting the properties of the nonlinear fractional programming. We prove that the optimum solution obtained by the proposed algorithm is the Nash equilibrium of the noncooperative game. We also analyze the tradeoff between EE and SE and derive closed-form expressions for EE and SE gaps.Comment: submitted to IET Communications. arXiv admin note: substantial text overlap with arXiv:1405.1963, arXiv:1407.155