The LTE specifications provide QoS for multimedia services with fast connectivity, high mobility and security. However, 3GPP specifications have not defined scheduling algorithms to exploit the LTE characteristics to support real time services. In this article we propose a two level scheduling scheme composed by cooperative game theory, a virtual token mechanism, and the well known algorithms EXP-RULE and Modified-Largest Weighted Delay Firs (M-LWDF) in downlink system. By using cooperative game theory such as bankruptcy game and Shapley value, the proposed mechanism works by forming coalitions between flow classes to distribute the bandwidth fairly among all of them. Both algorithms EXP-RULE and M-LWDF have been modified to use a virtual token mechanism to improve their performance, giving priority to real time flows. By taking the arrival rate of packets into account, the proposed mechanism partially included in previous schedulers has been adapted to this work to increase remarkably the performance of the resource allocation for real time flows. The performance evaluation is conducted in terms of system throughput, Packet loss ratio, total cell spectral efficiency, delay and fairness index.

No abstract

In 5G networks, specific requirements are defined on the periodicity of Synchronization Signaling (SS) bursts. This imposes a constraint on the maximum period a Base Station (BS) can be deactivated. On the other hand, BS densification is expected in 5G architecture. This will lead to an energy crunch if kept ignored. In this paper, we propose a distributed algorithm based on Reinforcement Learning (RL) that controls the states of the BSs while respecting the requirements of 5G. By considering different levels of Sleep Modes (SMs), the algorithm chooses how deep a BS can sleep according to the best switch-off SM level policy that maximizes the trade-off between energy savings and system delay. The latter is calculated based on the wake-up time required by the different SM levels. Results show that our algorithm performs better than the case of using only one type of SM. Furthermore, our simulations show a gain in energy savings up to 90% when the users are delay tolerant while respecting the periodicity of the SS bursts in 5G.

The LTE specification provides QoS of multimedia services with fast connectivity, high mobility and security. However, 3GPP specifications have not defined scheduling algorithms to support real time and non-real time application services. In this paper we propose a two level scheduling scheme composed by cooperative game concept and EXP-RULE scheduling algorithm. By using cooperative game theory such as bankruptcy game and Shapley value, the proposed mechanism works by forming coalition between flow classes to distribute the bandwidth fairly. To make a performance judgment, the proposed downlink scheduling scheme has been compared to other well known schedulers such as M-LWDF and PF. Simulation results show that the proposed scheme can improve the performance on the used metrics among services. The performance evaluation is conducted in terms of system throughput, packet loss ratio (PLR), cell spectral efficiency and fairness Index.

In this paper, we propose a sleep strategy for energyefficient 5G Base Stations (BSs) with multiple Sleep Mode (SM) levels to bring down energy consumption. Such management of energy savings is coupled with managing the Quality of Service (QoS) resulting from waking up sleeping BSs. As a result, a tradeoff exists between energy savings and delay. Unlike prior work that studies this problem for binary state BS (ON and OFF), this work focuses on multi-level SM environment, where the BS can switch to several SM levels. We propose a Q-Learning algorithm that controls the state of the BS depending on the geographical location and moving velocity of neighboring users in order to learn the best policy that maximizes the tradeoff between energy savings and delay. We evaluate the performance of our proposed algorithm with an online suboptimal algorithm that we introduce as well. Results show that the Q-Learning algorithm performs better with energy savings up to 92% as well as better delay performance than the heuristic scheme.

No abstract

In this paper a two level resource allocation scheme is proposed to enhance the Quality of Service (QoS) for multimedia services in LTE downlink system. It corresponds to a solution that combines cooperative game theory, a virtual token mechanism, and the EXP-RULE algorithm. By using cooperative game theory such as bankruptcy game and Shapley value, the proposed mechanism works by forming coalitions between flow classes to distribute bandwidth fairly. EXP-RULE algorithm has been modified to use a virtual token mechanism to improve its performance. By taking into account constraints such as Shapley value fairness and the virtual token robustness, the proposed mechanism can increase remarkably the performance for real time flows such as video and VoIP in downlink system. The performance evaluation is conducted in terms of system throughput, packet loss ratio (PLR), cell spectral efficiency and fairness index.Index Terms-Wireless networks, quality of service, long term evolution, cooperative game theory, shapley value.

Deploying mobile relays in public transportation is a simple yet effective way to avoid the electromagnetic insulation within vehicles and to increase the Quality of Service (QoS) perceived by passengers, which is sometimes low. Mobile relaying can be done by using an LTE/EPC 100%-compatible architecture. However, this solution induces extra-overhead. In this paper we evaluate the QoS of an LTE mobile relay architecture for public railway transport systems for two representative services: client-server requests and voice communications. We compare the performance of a direct transmission against a mobile relay architecture for different types of requests and different load conditions. This work, therefore, evaluates the mobile relay performance in terms of load time, throughput, packet loss ratio and end-to-end latency. Our findings show that a mobile relay architecture highly improves the QoS performance for train passengers. Furthermore, the gain is greater as the load increases.