Abd-Elhamid M. Taha

Uplink Scheduling in LTE and LTE-Advanced: Tutorial, Survey and Evaluation Framework

The choice of OFDM-based multi-carrier access techniques for LTE marked a fundamental and farsighted parting from preceding 3GPP networks. With OFDMA in the downlink and SC-FDMA in the uplink, LTE possesses a robust and adaptive multiple access scheme that facilitates many physical layer enhancements. Despite this flexibility, scheduling in LTE is a challenging functionality to design, especially in the uplink. Resource allocation in LTE is made complex, especially when considering its target packet-based services and mobility profiles, both current and emerging, in addition to the use of several physical layer enhancements. In this paper, we offer a tutorial on scheduling in LTE and its successor LTE-Advanced. We also survey representative schemes in the literature that have addressed the scheduling problem, and offer an evaluation methodology to be used as a basis for comparison between scheduling proposals in the literature.

Quality of service in 3GPP R12 LTE-advanced

Growing demand for mobile data traffic is challenging even the capacities of next generation wireless networks. In response, operators worldwide are expanding and updating their deployment. In turn, 3GPP continues to explore ways to empower operators with features for more capable, economic, and energy-efficient networks. Toward 3GPP Release 12, focus has shifted to accommodate the inevitable traffic explosion in both magnitude and traffic types. In this work, we highlight some of the features of LTE-Advanced Release 12 relevant to improving quality of service. Specifically, we focus on solutions explored to enhance network capacity and service delivery in terms of offloading, improved services, and improved congestion control.

Using smart vehicles for localizing isolated Things

Elementary to the success of the Internet of Things (IoT) is the capability to accurately and efficiently localize its network components, information, and processes. In this paper, we focus on enabling localization of Things that have limited capabilities deployed in isolated areas. Specifically, we explore the scenario where the deployment or the utilization of dedicated anchor nodes becomes costly or practically unfeasible, and where the dependence on multi-hop localization techniques becomes inevitable. We further advocate the use of emerging IoT components such as smart vehicles, capable of self-localization and short-range communication. The proposed scheme thus illustrates the feasibility of a multi-hop wireless localization scheme dependent on mobile anchors (reference points). A key advantage of the proposed scheme is overcoming collinear trajectory (flip-ambiguity) problem, which arises whenever the smart vehicle moves in a straight trajectory. A Kalman Filter (KF) is used to decrease the location error introduced from the multi-hopping during the localization process. Through simulation, we show that the use of our localization scheme with KF reduces errors by 31% compared to localization using anchors from a single direction and 16% compared to a weighted means approach. Moreover, our scheme with KF consistently outperforms the typical range-based DV-Distance scheme with fixed anchors.

Coalitional relay selection game to extend battery lifetime of multi-standard mobile terminals

Multi-standard mobile terminals (MTs) allow mobile users to experience ubiquitous connectivity and better quality of service. However, these advances come at a price of higher power consumption for MTs due to holding multiple active interfaces. In this paper, we apply multihop relaying through pervasive short range interfaces (e.g., Bluetooth, WiMedia. etc.) in the presence of an infrastructure network (e.g., LTE, WiFi, etc.) to extend the battery lifetime of multi-standard MTs. To this end, MTs exchange context information (conveying channel state information, battery level, etc.) and, whenever beneficial, form a coalition, pool their resources, and perform their tasks cooperatively to enhance their efficiency. We introduce a novel utility function to assess the profitability of cooperation. To incentivize MTs to cooperate, the achieved common utility of the coalition can be distributed among the cooperative MTs by means of energy credits using a solution concept from coalitional game theory. The simulation results validate the effectiveness of the proposed approach to extend the battery lifetime of MTs to more than double.

Benchmarking message authentication code functions for mobile computing

With the increased popularity of both Internet and mobile computing, several security mechanisms, each using various cryptography functions, have been proposed to ensure that future generation Internets will guarantee both authenticity and data integrity. These functions are usually computationally intensive resulting in large communication delays and energy consumption for the power-limited mobile systems. The functions are also implemented in variety of ways with different resource demands, and may run differently depending on platform. Since communications within the next generation Internet are to be secured, it is important for a mobile system to be suited to the function that provide sufficient communication security while maintaining both power-efficiency and delay requirements. This paper benchmarks mobile systems with cryptographic functions used in message authentication. This paper also introduces a metric, namely apparent processing, that makes benchmarking meaningful for mobile systems with multiple processing cores or utilizing hardware-based cryptography. In addition, this paper discusses some of evaluated functions computational characteristics observed through benchmarking on selected mobile computing architectures.

Does multi-hop communication enhance localization accuracy?

Estimating the location of sensor nodes in wireless sensor networks is a fundamental problem, as sensor node locations play a critical role in a variety of applications. In many cases the area covered is very large making it impossible to localize all sensor nodes using single-hop localization techniques. A solution to this problem is to use a multi-hop localization technique to estimate sensor node positions. Multi-hop localization techniques are classified into two main categories: range-based and range-free. Despite the numerous existing localization techniques, the fundamental behavior of multi-hop localization is yet to be fully examined. The aim of this paper is to study the effect of errors in a multi-hop localization environment and how this impacts localization accuracy. There has been a general belief that a fewer number of hops results in higher accuracy. Through different experiments on two generic localization techniques representing both categories of localization schemes, we show that such belief is not true in all cases, as in dense environments often using shorter hops gives better accuracy.

Towards prolonged lifetime for large-scale Information-Centric Sensor Networks

Information-Centric Sensor Networks (ICSNs) are a class of context-aware communication networks that provide an infrastructure for knowledge-based intelligent information service provisioning to anyone, anywhere and at any time. It provides the sensed information to the end-user based on application requirements. To cater to the needs of ICSNs applications, WSNs may need to be deployed on a very large scale. Maintaining network connectivity and longevity in such a large scale deployment of sensor nodes, while catering to the application and service requirements of the ICSN is a challenging task because sensor nodes are very resource constrained in terms of power, communication range and processing capabilities. Hence, we propose the use of cognitive nodes in the underlying WSN, which can help to achieve better management of the sensor networks resources. The cognitive nodes make use of the requested information to learn the dynamic network environment, and make decisions based on the application requirements and current network conditions. Cognitive nodes will use information stored in their knowledge base to help with resource management in the sensor network while catering to the service requirements of the ICSN. The main contribution of this work is to provide a strategy for their deployment in large-scale WSNs used in ICSN applications.

A two-phase auction-based fair resource allocation for underlaying D2D communications

Interference coordination while sharing cellular radio resources with Device-to-Device (D2D) pairs needs to be done in the short LTE scheduling period of 1 ms. In this paper, we propose a fast, two-phase auction based, fair and interference aware resource allocation algorithm (TAFIRA) for underlaying D2D communication. TAFIRA can be used to minimize the interference both at the evolved Node B (eNB) and the receiver of the D2D pairs while simultaneously maintaining a target system sum rate and ensuring fair allocation of cellular resources among D2D pairs. We compare TAFIRA with a MInimum Knapsack based Interference Resource Allocation algorithm (MIKIRA) and a random allocation technique. The time complexity of TAFIRA on average is O(m2n), where m and n are the number of D2D pairs and number of cellular users respectively. Our simulation results how that, TAFIRA obtains a much better system sum rate while incurring very little increased interference at the eNB and the D2D receivers when compared with MIKIRA and the random approach. TAFIRA also shows much more fairness in allocating cellular resources among the D2D pairs when compared with MIKIRA.

Handover-related self-optimization in femtocells

Femtocells enable LTE technology when deployed in large numbers. However, every femtocell needs to self-optimize its control parameters in response to surrounding dynamic events. This paper focuses on self-optimization use cases related to handovers in LTE femtocell networks including: handover self-optimization, call admission control self-optimization and load balancing self-optimization. These three use cases can interact either constructively or destructively. To the best of our knowledge, no previous work has addressed the nature of this interaction. Therefore, we survey proposed schemes for each one of these handover-related self-optimization use cases after which three representative schemes have been identified. These schemes are used in our interaction study using our in-house MATLAB-written and LTE compliant simulation environment. Based on interaction simulation results, we recommend a set of guidelines to follow when coordinating between these interacting handover-related self-optimization use cases in LTE femtocell networks.

Reducing the complexity of Resource Allocation for underlaying Device-to-Device communications

Sharing resources between Long Term Evolution (LTE) cellular users and Device-to-Device (D2D) pairs comes at the cost of increased interference. In this paper, we propose a Minimum Knapsack-based Interference-aware Resource Allocation (MIKIRA) approach to show that a channel sharing approach can be used to increase system sum rate, minimize the interference both at the evolved Node B (eNB) and the receiver of the D2D pairs, and most importantly achieve a good signal quality at the eNB in lower time complexity in an LTE cellular network. We compare the system sum rate, interference and Signal-to-Interference and Noise Ratio (SINR) obtained by MIKIRA with a bipartite graph-based approach (GRA) for resource allocation and a random allocation approach. ¿From the results we find that MIKIRA shows improved performance when compared to other approaches in all of the metrics we used in the simulation. MIKIRA is more efficient in terms of time complexity (O(n2 log(n))) when compared with the GRA (O(n3)); and also results in higher quality signals as the SINR achieved at the eNB is much better than the other two approaches.