Device Discovery Schemes for Energy-efficient Cluster Head Rotation in D2D

 In this paper, novel device discovery approaches for the Cluster Head Rotation, which is a state-of-the-art method for the Device-to-Device communication, are proposed. The device discovery is the process to detect and to include new devices in the Device-to-Device communication. The proposed device discovery is aimed to attain energy efficiency for the communication devices. We propose two schemes for the device discovery: eNB-assisted and independent device discovery. Compared to previous work, the proposed device discovery is utilizing the cluster head rotation method, to achieve better energy efficiency. In this work, several simulations were performed and discussed for both schemes. In the first simulation, the device energy consumption is examined. After that, the number of devices that get rejected is studied. The device discovery processes in multi cluster head scenario, which is Cluster Head Rotation, are examined in this paper. The result of the simulation shows that eNB-assisted device discovery can provide better energy efficiency. Also, the number of rejected devices of the eNB-assisted device discovery is slightly lower than independent device discovery

Energy Efficiency and Sum Rate Tradeoffs for Massive MIMO Systems with Underlaid Device-to-Device Communications

In this paper, we investigate the coexistence of two technologies that have been put forward for the fifth generation (5G) of cellular networks, namely, network-assisted device-to-device (D2D) communications and massive MIMO (multiple-input multiple-output). Potential benefits of both technologies are known individually, but the tradeoffs resulting from their coexistence have not been adequately addressed. To this end, we assume that D2D users reuse the downlink resources of cellular networks in an underlay fashion. In addition, multiple antennas at the BS are used in order to obtain precoding gains and simultaneously support multiple cellular users using multiuser or massive MIMO technique. Two metrics are considered, namely the average sum rate (ASR) and energy efficiency (EE). We derive tractable and directly computable expressions and study the tradeoffs between the ASR and EE as functions of the number of BS antennas, the number of cellular users and the density of D2D users within a given coverage area. Our results show that both the ASR and EE behave differently in scenarios with low and high density of D2D users, and that coexistence of underlay D2D communications and massive MIMO is mainly beneficial in low densities of D2D users.Comment: 30 pages, 10 figures, Submitte

Unmanned Aerial Vehicle with Underlaid Device-to-Device Communications: Performance and Tradeoffs

In this paper, the deployment of an unmanned aerial vehicle (UAV) as a flying base station used to provide on the fly wireless communications to a given geographical area is analyzed. In particular, the co-existence between the UAV, that is transmitting data in the downlink, and an underlaid device-todevice (D2D) communication network is considered. For this model, a tractable analytical framework for the coverage and rate analysis is derived. Two scenarios are considered: a static UAV and a mobile UAV. In the first scenario, the average coverage probability and the system sum-rate for the users in the area are derived as a function of the UAV altitude and the number of D2D users. In the second scenario, using the disk covering problem, the minimum number of stop points that the UAV needs to visit in order to completely cover the area is computed. Furthermore, considering multiple retransmissions for the UAV and D2D users, the overall outage probability of the D2D users is derived. Simulation and analytical results show that, depending on the density of D2D users, optimal values for the UAV altitude exist for which the system sum-rate and the coverage probability are maximized. Moreover, our results also show that, by enabling the UAV to intelligently move over the target area, the total required transmit power of UAV while covering the entire area, is minimized. Finally, in order to provide a full coverage for the area of interest, the tradeoff between the coverage and delay, in terms of the number of stop points, is discussed.Comment: accepted in the IEEE Transactions on Wireless Communication

Channel Selection for Network-assisted D2D Communication via No-Regret Bandit Learning with Calibrated Forecasting

We consider the distributed channel selection problem in the context of device-to-device (D2D) communication as an underlay to a cellular network. Underlaid D2D users communicate directly by utilizing the cellular spectrum but their decisions are not governed by any centralized controller. Selfish D2D users that compete for access to the resources construct a distributed system, where the transmission performance depends on channel availability and quality. This information, however, is difficult to acquire. Moreover, the adverse effects of D2D users on cellular transmissions should be minimized. In order to overcome these limitations, we propose a network-assisted distributed channel selection approach in which D2D users are only allowed to use vacant cellular channels. This scenario is modeled as a multi-player multi-armed bandit game with side information, for which a distributed algorithmic solution is proposed. The solution is a combination of no-regret learning and calibrated forecasting, and can be applied to a broad class of multi-player stochastic learning problems, in addition to the formulated channel selection problem. Analytically, it is established that this approach not only yields vanishing regret (in comparison to the global optimal solution), but also guarantees that the empirical joint frequencies of the game converge to the set of correlated equilibria.Comment: 31 pages (one column), 9 figure

Clustering algorithm for D2D communication in next generation cellular networks : thesis presented in partial fulfilment of the requirements for the degree of Doctor of Philosophy in Engineering, Massey University, Auckland, New Zealand

Next generation cellular networks will support many complex services for smartphones, vehicles, and other devices. To accommodate such services, cellular networks need to go beyond the capabilities of their previous generations. Device-to-Device communication (D2D) is a key technology that can help fulfil some of the requirements of future networks. The telecommunication industry expects a significant increase in the density of mobile devices which puts more pressure on centralized schemes and poses risk in terms of outages, poor spectral efficiencies, and low data rates. Recent studies have shown that a large part of the cellular traffic pertains to sharing popular contents. This highlights the need for decentralized and distributive approaches to managing multimedia traffic. Content-sharing via D2D clustered networks has emerged as a popular approach for alleviating the burden on the cellular network. Different studies have established that D2D communication in clusters can improve spectral and energy efficiency, achieve low latency while increasing the capacity of the network. To achieve effective content-sharing among users, appropriate clustering strategies are required. Therefore, the aim is to design and compare clustering approaches for D2D communication targeting content-sharing applications. Currently, most of researched and implemented clustering schemes are centralized or predominantly dependent on Evolved Node B (eNB). This thesis proposes a distributed architecture that supports clustering approaches to incorporate multimedia traffic. A content-sharing network is presented where some D2D User Equipment (DUE) function as content distributors for nearby devices. Two promising techniques are utilized, namely, Content-Centric Networking and Network Virtualization, to propose a distributed architecture, that supports efficient content delivery. We propose to use clustering at the user level for content-distribution. A weighted multi-factor clustering algorithm is proposed for grouping the DUEs sharing a common interest. Various performance parameters such as energy consumption, area spectral efficiency, and throughput have been considered for evaluating the proposed algorithm. The effect of number of clusters on the performance parameters is also discussed. The proposed algorithm has been further modified to allow for a trade-off between fairness and other performance parameters. A comprehensive simulation study is presented that demonstrates that the proposed clustering algorithm is more flexible and outperforms several well-known and state-of-the-art algorithms. The clustering process is subsequently evaluated from an individual user’s perspective for further performance improvement. We believe that some users, sharing common interests, are better off with the eNB rather than being in the clusters. We utilize machine learning algorithms namely, Deep Neural Network, Random Forest, and Support Vector Machine, to identify the users that are better served by the eNB and form clusters for the rest of the users. This proposed user segregation scheme can be used in conjunction with most clustering algorithms including the proposed multi-factor scheme. A comprehensive simulation study demonstrates that with such novel user segregation, the performance of individual users, as well as the whole network, can be significantly improved for throughput, energy consumption, and fairness

Game Theory for Multi-Access Edge Computing:Survey, Use Cases, and Future Trends

Game theory (GT) has been used with significant success to formulate, and either design or optimize, the operation of many representative communications and networking scenarios. The games in these scenarios involve, as usual, diverse players with conflicting goals. This paper primarily surveys the literature that has applied theoretical games to wireless networks, emphasizing use cases of upcoming multiaccess edge computing (MEC). MEC is relatively new and offers cloud services at the network periphery, aiming to reduce service latency backhaul load, and enhance relevant operational aspects such as quality of experience or security. Our presentation of GT is focused on the major challenges imposed by MEC services over the wireless resources. The survey is divided into classical and evolutionary games. Then, our discussion proceeds to more specific aspects which have a considerable impact on the game's usefulness, namely, rational versus evolving strategies, cooperation among players, available game information, the way the game is played (single turn, repeated), the game's model evaluation, and how the model results can be applied for both optimizing resource-constrained resources and balancing diverse tradeoffs in real edge networking scenarios. Finally, we reflect on lessons learned, highlighting future trends and research directions for applying theoretical model games in upcoming MEC services, considering both network design issues and usage scenarios

Conception d'un modèle novateur améliorant la performance dans les réseaux de la sécurité publique sur LTE hétérogènes

Durant les situations d’urgences, la disponibilité des moyens de télécommunications est cruciale et indispensable pour les usagers des réseaux de la Sécurité Publique (PSN). En revanche, durant de tels moments, le besoin en échange d’information croît d’une façon spectaculaire. Par conséquent, l’accès au médium radio devient congestionné très rapidement. Malheureusement, durant ces moments, les ressources dédiées aux réseaux (PSN) ne semblent pas être suffisantes pour satisfaire toutes les requêtes d’établissement des nouveaux bearers. Les réseaux LTE viennent donc contribuer à la résolution de cette problématique, en offrant l’accès à la Radio Commerciale Partagée pour le réseau PSN, avec une certaine priorisation, afin d’améliorer les communications PSN lors des situations d’urgences. Néanmoins, cet accès ne doit pas accaparer toutes les ressources du réseau commercial. De plus, la technologie LTE permet l’utilisation des communications Device-to-Device qui consiste à échanger l’information directement entre les équipements sans avoir à passer par l’eNodeB. Les communications D2D doivent donc être exploitées pour contourner les problèmes de congestion, surtout lors des désastres. Par ailleurs, l’amélioration de la performance des réseaux PSN ne se limite pas dans la gestion efficace des ressources radio. L’allocation des ressources de bande passante au niveau du réseau Backhaul et du réseau coeur LTE doit aussi être améliorée. Dans cette thèse un nouveau modèle novateur a été conçu pour l’amélioration de la performance dans les réseaux de la sécurité publique sur les réseaux LTE hétérogènes. Ce modèle qui compte dix solutions, intervient sur les trois réseaux composant le réseau LTE, à savoir le réseau d’accès, le réseau Backhaul et le réseau coeur LTE. Nos différentes solutions ont toutes été validées par simulations, et ont toutes apporté une amélioration par rapport à aux approches classiques ou par rapport à d’autres approches existantes dans la littérature