Elias Yaacoub

A Survey on Uplink Resource Allocation in OFDMA Wireless Networks

OFDMA has been selected as the multiple access scheme for state-of-the-art wireless communication systems. Efficient resource allocation in OFDMA wireless networks is essential in order to meet the quality of service requirements of emerging services. In this paper, a survey of resource allocation and scheduling schemes in OFDMA wireless networks is presented. The focus is on the uplink direction. Resource allocation is surveyed in various scenarios: centralized and distributed, instantaneous and ergodic, optimal and suboptimal, single cell and multicell, cooperative and non-cooperative, in addition to different combinations of these variants. Directions for future research are outlined.

Toward Massive Machine Type Cellular Communications

Cellular networks have been engineered and optimized to carrying ever-increasing amounts of mobile data, but over the last few years, a new class of applications based on machine-centric communications has begun to emerge. Automated devices such as sensors, tracking devices, and meters, often referred to as machine-to-machine (M2M) or machine-type communications (MTC), introduce an attractive revenue stream for mobile network operators, if a massive number of them can be efficiently supported. The novel technical challenges posed by MTC applications include increased overhead and control signaling as well as diverse application-specific constraints such as ultra-low complexity, extreme energy efficiency, critical timing, and continuous data intensive uploading. This article explains the new requirements and challenges that large-scale MTC applications introduce, and provides a survey of key techniques for overcoming them. We focus on the potential of 4.5G and 5G networks to serve both the high data rate needs of conventional human-type communication (HTC) subscribers and the forecasted billions of new MTC devices. We also opine on attractive economic models that will enable this new class of cellular subscribers to grow to its full potential.

A Game Theoretical Formulation for Proportional Fairness in LTE Uplink Scheduling

Uplink scheduling in LTE systems is considered. A game theoretical formulation is derived where the scheduling problem is represented as a Nash bargaining solution. An algorithm to implement the proposed scheduling scheme is presented. Throughput and fairness analysis are performed via simulations. Results show that channel aware scheduling schemes outperform the round-robin scheme, but a tradeoff must be made between the increase of total throughput and fairness towards the different users.

Energy-Aware Cooperative Content Distribution over Wireless Networks: Design Alternatives and Implementation Aspects

This paper presents a comprehensive overview on the area of energy-aware common content distribution over wireless networks with mobile-to-mobile cooperation. It is assumed that a number of mobile terminals (MTs) that are geographically close to each other are interested in downloading the same content from a server via a base station using a long-range wireless technology. Selected MTs download the content directly from the base station and transmit it to other MTs using a short-range wireless technology. This cooperation can lead to significant performance gains since short-range wireless technologies are energy efficient and provide higher data rates due to the geographical proximity among the MTs. In this paper, we highlight the main alternatives that shape the design of cooperative content distribution architectures with focus on energy efficiency. These include content segmentation, long-range and short-range distribution strategies, grouping of the MTs into cooperating clusters, single hop and multihop communications among the MTs, resource allocation, fairness considerations, and network dynamics. We also discuss various methods commonly utilized for developing content distribution algorithms and evaluating network performance. Finally, we present sample results for selected network scenarios, discuss related standardization activities, and highlight future research directions.

Optimized Smart Grid Energy Procurement for LTE Networks Using Evolutionary Algorithms

Energy efficiency aspects in cellular networks can contribute significantly to reducing worldwide greenhouse gas emissions. The base station (BS) sleeping strategy has become a well-known technique to achieve energy savings by switching off redundant BSs mainly for lightly loaded networks. Moreover, introducing renewable energy as an alternative power source has become a real challenge among network operators. In this paper, we formulate an optimization problem that aims to maximize the profit of Long-Term Evolution (LTE) cellular operators and to simultaneously minimize the CO2 emissions in green wireless cellular networks without affecting the desired quality of service (QoS). The BS sleeping strategy lends itself to an interesting implementation using several heuristic approaches, such as the genetic (GA) and particle swarm optimization (PSO) algorithms. In this paper, we propose GA-based and PSO-based methods that reduce the energy consumption of BSs by not only shutting down underutilized BSs but by optimizing the amounts of energy procured from different retailers (renewable energy and electricity retailers), as well. A comparison with another previously proposed algorithm is also carried out to evaluate the performance and the computational complexity of the employed methods.

Wireless sensor network for real-time air pollution monitoring

This paper presents an ambient real-time air quality monitoring system. The system consists of several distributed monitoring stations that communicate wirelessly with a backend server using machine-to-machine communication. Each station is equipped with gaseous and meteorological sensors as well as data logging and wireless communication capabilities. The backend server collects real time data from the stations and converts it into information delivered to users through web portals and mobile applications. The system is implemented in pilot phase and four solar-powered stations are deployed over an area of 1 km2. Data over four months has been collected and performance analysis and assessment are performed. As the historical data bank becomes richer, more sophisticated operations can be performed.

Energy-efficient Device-to-Device communications in LTE public safety networks

Device-to-Device communications are studied in the framework of LTE public safety networks. We propose a model where devices cooperate on the short range by forming coalitions for the purpose of energy efficiency. In each coalition, a device is selected to communicate with the base station on the long range. Coalition formation is investigated both for the uplink and downlink directions. Simulation results show that significant energy savings can be achieved with the proposed approach compared to the non-collaborative case, in addition to reduced delay and enhanced quality-of-service (QoS).

A utility minimization approach for energy‐aware cooperative content distribution with fairness constraints

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Low complexity scheduling algorithms for the LTE uplink

Uplink scheduling in LTE systems is considered. Two low complexity heuristic algorithms for suboptimal subcarrier allocation are proposed and compared to other algorithms in the literature. Throughput and fairness analysis of the different algorithms are performed via monte-carlo simulations. The proposed algorithms are utility maximizing algorithms that can be used with various utility functions. Simulations show the superiority of the proposed algorithms and that promising results can be achieved by linear complexity algorithms.

QoE Enhancement of SVC Video Streaming Over Vehicular Networks Using Cooperative LTE/802.11p Communications

Real-time streaming of scalable video coded (SVC) videos in vehicular networks is investigated, and novel cooperative vehicle-to-vehicle (V2V) communication methods are proposed. The proposed techniques are based on grouping the moving vehicles into cooperative clusters. Within each cluster, the long term evolution (LTE) system is used to send the data over long range cellular links to a selected cluster head, which multicasts the received video over IEEE 802.11p to vehicles in its cluster. Error concealment techniques are used to compensate the loss of frames that are not delivered on time for real-time video streaming. In addition, resource allocation to select the best subcarriers for LTE transmission is performed in order to enhance the received video quality. Moreover, metrics related to both quality of service (QoS) and quality of experience (QoE) are studied and analyzed for various video sequences of different characteristics. The V2V video streaming techniques are extended to the case of vehicle-to-infrastructure (V2I) communications. Simulation results show that the proposed methods lead to enhanced QoS and QoE compared to the non collaborative scenarios, and their performance tradeoffs compared to recent methods from the literature are discussed.