Game Theoretic Network Coding-aided MAC for Data Dissemination towards Energy Efficiency

In this paper we propose game theoretic Medium Access Control (MAC) strategies for data dissemination scenarios. In particular, we use energy-based utility functions that inherently imply power-awareness, while we consider network coding techniques to eliminate the necessity of exchanging acknowledgement control packets. Simulation results show that our proposed strategies enhance the energy efficiency of the system and reduce the dissemination completion time compared to an optimized standard protocol.Comment: accepted at IEEE CoCoNet (Cooperative and Cognitive Mobile Networks) Workshop 2012, co-located with IEEE ICC 2012 in Ottawa, Canad

Up-link performance of the DQRUMA MAC protocol in a realistic indoor environment for W-ATM networks

This paper evaluates by simulation the performance of the distributed queuing request update multiple access (DQRUMA) MAC protocol in a realistic indoor environment. This protocol has been simulated in conjunction with a type-II hybrid-ARQ protocol based on punctured R-S codes for the LLC layer. The analysis was carried out for a multicarrier modulation scheme (OFDM) with QPSK modulation on each carrier. The hidden Markov model (HMM) is used for modelling the physical layer of the system. The performance of the protocol in terms of throughput, mean delay, CLR and p.d.f. of the delay is presented. The pseudo-Bayesian algorithm as well as harmonic back-off are applied to calculate the retransmission probability for the backlogged users.Peer ReviewedPostprint (published version

Scalable RAN Virtualization in Multi-Tenant LTE-A Heterogeneous Networks (Extended version)

Cellular communications are evolving to facilitate the current and expected increasing needs of Quality of Service (QoS), high data rates and diversity of offered services. Towards this direction, Radio Access Network (RAN) virtualization aims at providing solutions of mapping virtual network elements onto radio resources of the existing physical network. This paper proposes the Resources nEgotiation for NEtwork Virtualization (RENEV) algorithm, suitable for application in Heterogeneous Networks (HetNets) in Long Term Evolution-Advanced (LTE-A) environments, consisting of a macro evolved NodeB (eNB) overlaid with small cells. By exploiting Radio Resource Management (RRM) principles, RENEV achieves slicing and on demand delivery of resources. Leveraging the multi-tenancy approach, radio resources are transferred in terms of physical radio Resource Blocks (RBs) among multiple heterogeneous base stations, interconnected via the X2 interface. The main target is to deal with traffic variations in geographical dimension. All signaling design considerations under the current Third Generation Partnership Project (3GPP) LTE-A architecture are also investigated. Analytical studies and simulation experiments are conducted to evaluate RENEV in terms of network's throughput as well as its additional signaling overhead. Moreover we show that RENEV can be applied independently on top of already proposed schemes for RAN virtualization to improve their performance. The results indicate that significant merits are achieved both from network's and users' perspective as well as that it is a scalable solution for different number of small cells.Comment: 40 pages (including Appendices), Accepted for publication in the IEEE Transactions on Vehicular Technolog

Spectral Efficient and Energy Aware Clustering in Cellular Networks

The current and envisaged increase of cellular traffic poses new challenges to Mobile Network Operators (MNO), who must densify their Radio Access Networks (RAN) while maintaining low Capital Expenditure and Operational Expenditure to ensure long-term sustainability. In this context, this paper analyses optimal clustering solutions based on Device-to-Device (D2D) communications to mitigate partially or completely the need for MNOs to carry out extremely dense RAN deployments. Specifically, a low complexity algorithm that enables the creation of spectral efficient clusters among users from different cells, denoted as enhanced Clustering Optimization for Resources' Efficiency (eCORE) is presented. Due to the imbalance between uplink and downlink traffic, a complementary algorithm, known as Clustering algorithm for Load Balancing (CaLB), is also proposed to create non-spectral efficient clusters when they result in a capacity increase. Finally, in order to alleviate the energy overconsumption suffered by cluster heads, the Clustering Energy Efficient algorithm (CEEa) is also designed to manage the trade-off between the capacity enhancement and the early battery drain of some users. Results show that the proposed algorithms increase the network capacity and outperform existing solutions, while, at the same time, CEEa is able to handle the cluster heads energy overconsumption

Weighted proportional fairness and pricing based resource allocation for uplink offloading using IP flow mobility

Mobile data offloading has been proposed as a solution for the network congestion problem that is continuously aggravating due to the increase in mobile data demand. However, the majority of the state-of-the-art is focused on the downlink offloading, while the change of mobile user habits, like mobile content creation and uploading, makes uplink offloading a rising issue. In this work we focus on the uplink offloading using IP Flow Mobility (IFOM). IFOM allows a LTE mobile User Equipment (UE) to maintain two concurrent data streams, one through LTE and the other through WiFi access technology, that presents uplink limitations due to the inherent fairness design of IEEE 802.11 DCF by employing the CSMA/CA scheme with a binary exponential backoff algorithm. In this paper, we propose a weighted proportionally fair bandwidth allocation algorithm for the data volume that is being offloaded through WiFi, in conjunction with a pricing-based rate allocation for the rest of the data volume needs of the UEs that are transmitted through the LTE uplink. We aim to improve the energy efficiency of the UEs and to increase the offloaded data volume under the concurrent use of access technologies that IFOM allows. In the weighted proportionally fair WiFi bandwidth allocation, we consider both the different upload data needs of the UEs, along with their LTE spectrum efficiency and propose an access mechanism that improves the use of WiFi access in uplink offloading. In the LTE part, we propose a two-stage pricing-based rate allocation under both linear and exponential pricing approaches, aiming to satisfy all offloading UEs regarding their LTE uplink access. We theoretically analyse the proposed algorithms and evaluate their performance through simulations. We compare their performance with the 802.11 DCF access scheme and with a state-of-the-art access algorithm under different number of offloading UEs and for both linear and exponential pricing-based rate allocation for the LTE uplink. Through the evaluation of energy efficiency, offloading capabilities and throughput performance, we provide an improved uplink access scheme for UEs that operate with IFOM for uplink offloading.Peer ReviewedPreprin

Resource allocation techniques for heterogeneous networks under user misbehavior

©2016 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.In this letter we focus on the uplink offloading with IP Flow Mobility (IFOM). With IFOM a User Equipment (UE) is able to maintain concurrently two data streams, one through LTE and the other through WiFi. We consider the existence of malicious UEs that aim to exploit the WiFi bandwidth against their truthful peers, in order to upload less data through the energy demanding LTE uplink and a reputation based method is proposed to combat the selfish operation. The WiFi bandwidth is allocated based on weighted proportional fairness and the LTE rate is defined through an exponential pricing algorithm. We theoretically analyse our approach and evaluate the performance of the malicious and the truthful UEs in terms of energy efficiency and throughput, through simulations. We show that while the malicious UEs present better energy efficiency before being detected, their performance is significantly degraded with the proposed reaction method.Peer ReviewedPostprint (author's final draft

A Novel Handover Decision Policy for Reducing Power Transmissions in the two-tier LTE network

Femtocells are attracting a fast increasing interest nowadays, as a promising solution to improve indoor coverage, enhance system capacity, and lower transmit power. Technical challenges still remain, however, mainly including interference, security and mobility management, intercepting wide deployment and adoption from mobile operators and end users. This paper describes a novel handover decision policy for the two-tier LTE network, towards reducing power transmissions at the mobile terminal side. The proposed policy is LTE backward-compatible, as it can be employed by suitably adapting the handover hysteresis margin with respect to a prescribed SINR target and standard LTE measurements. Simulation results reveal that compared to the widely-adopted strongest cell policy, the proposed policy can greatly reduce the power consumption at the LTE mobile terminals, and lower the interference network-wide

An energy-centric handover decision algorithm for the integrated LTE macrocell–femtocell network

Femtocells are attracting a fast increasing interest nowadays, as a promising solution to improve indoor coverage and system capacity. Due to the short transmit-receive distance, femtocells can greatly lower transmit power, prolong handset battery life, and enhance the user-perceived Quality of Service (QoS). On the other hand, technical challenges still remain, mainly including interference mitigation, security and mobility management, intercepting wide deployment and adoption by both mobile operators and end users. This paper introduces a novel energy-centric handover decision policy and its accompanied algorithm, towards minimizing the power consumption at the mobile terminal side in the integrated LTE macrocell–femtocell network. The proposed policy is shown to extend the widely-adopted strongest cell policy, by suitably adapting the handover hysteresis margin in accordance with standardized LTE measurements on the tagged user’s neighbor cells. Performance evaluation results show that significantly lower interference and power consumption can be attained for the cost of a moderately increased number of network-wide handover executions events

Game-theoretic infrastructure sharing in multioperator cellular networks

©2016 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.The introduction of fourth-generation wireless technologies has fueled the rapid development of cellular networks, significantly increasing the energy consumption and the expenditures of mobile network operators (MNOs). In addition, network underutilization during low-traffic periods (e.g., night zone) has motivated a new business model, namely, infrastructure sharing, which allows the MNOs to have their traffic served by other MNOs in the same geographic area, thus enabling them to switch off part of their network. In this paper, we propose a novel infrastructure-sharing algorithm for multioperator environments, which enables the deactivation of underutilized base stations during low-traffic periods. Motivated by the conflicting interests of the MNOs and the necessity for effective solutions, we introduce a game-theoretic framework that enables the MNOs to individually estimate the switching-off probabilities that reduce their expected financial cost. Our approach reaches dominant strategy equilibrium, which is the strategy that minimizes the cost of each player. Finally, we provide extensive analytical and experimental results to estimate the potential energy and cost savings that can be achieved in multioperator environments, incentivizing the MNOs to apply the proposed scheme.Peer ReviewedPostprint (author's final draft