Mohamed Ashour

A preprocessing dependent image theory based ray tracing algorithm for indoor coverage solution

Hot spot coverage requirements of indoor environments necessitate adequate network platforms and optimal network planning. Optimal network planning imposes numerous iterative computations and evaluations of network coverage until the best antenna layout is achieved. Therefore, accurate and scalable indoor propagation models become of the ultimate essence. In this paper, image theory adopting a feasible reflection region concept is significantly enhanced using a pre-processing approach. The proposed method stores each mirrored image location, the corresponding feasible reflection region boundaries and the angles between walls of the indoor environment. Received power is calculated using stored data significantly reducing computational complexity in terms of the number of wall intersection tests that are necessary for coverage computations. The preprocessing approach is tested in different indoor configurations with multiple antennas. Simulation results confirm the superior accuracy of the proposed approach as well as the major complexity gain attained relative to other image theory based approaches.

Indoor Distributed Antenna System Planning with Optimized Antenna Power Using Genetic Algorithm

Distributed Antenna System (DAS) promises an attractive solution to cope with the increasing demand for high data rate services inside building. DAS divides the indoor Base Station power among a group of spatially separated antennas that are connected to the BS. The power sharing makes the planning of (DAS) more challenging compared to other wireless networks. The previous To simplify the problem DAS planning approaches divided power equally among the antennas and focused on finding the optimal number and locations of antennas. This paper optimizes the transmitted power of the DAS antennas along with their location and shows that this will enhance the performance compared to the equal power structure. The paper formulates the DAS planning problem as an optimization problem that considers the power division among antennas. The optimization aims to minimize the deployment cost and the power leakage outside the building while the maximizing the average data rate and the indoor coverage. To deal with these conflicting objectives and with the non-convexity of the formulated function, the paper develops meta-heuristic genetic algorithm with novel mutation and crossover methods that are customized to this problem.

Multi-scale analysis of generalised processor sharing queues with long-range-dependent traffic inputs and variable service rates

An analytical technique is provided to estimate queue-length and delay distributions for multi-queue systems using generalised processor sharing discipline with time-correlated variable service rates, based on two-dimensional multi-level decoupling. First, temporal decomposition is used to convert the time-correlated queuing problem into a set of sub-problems over several timescales. Subsequently, queue decomposition exploits the queue weight dependencies to convert a multi-queue problem into a set of single-queue problems. The core of the analysis lies in estimating the multi-scale service rate models for each of these queues. The authors show the hierarchy of this estimation and the dependency of the queue service rate on the unused capacity of the other queues and their weights. Simulation and analytical results on queue and delay survivor functions are in good agreement.

Report Success Probability/Battery Liftime Analysis of Dense IEEE 802.15.4-Based Metering Networks With Hidden Nodes

IEEE 802.15.4 and its amendments are among the leading candidates as enabling wireless technologies for metering networks. In a typical IEEE 802.15.4-based metering network, thousands of meter transceivers utilize CSMA/CA to send their metered data to a base station collector. With such enormous scale of devices competing for medium access, it becomes inevitable that meters might occasionally fail in reporting their data successfully. This could be attributed to consistent failure to grab access to the highly loaded shared medium or due to packet collision at the base station collector. Collisions occur due to synchronized channel access from meters within the same collision domain or due to hidden nodes across different collision domains. In this paper, a simple analytical model to evaluate the report success probability as well as meters’ battery lifetime within IEEE 802.15.4-based metering networks is introduced. The model quantifies the hidden node problem in terms of the average percentage of hidden transceivers with respect to each meter device within the network. Comparison with an OMNET++ simulation model shows that the presented analysis behaves as an upper bound on the report success probability. The model is then utilized for proper configuration of the IEEE 802.15.4 network given a target report success probability performance. It is shown that the expected battery lifetime of meters could be optimized by controlling the percentage of hidden nodes combined with proper setting of the maximum number of allowable backoff attempts by each meter.

Optimized transmitted antenna power indoor planning using distributed antenna systems

This paper aims to optimize the indoor planning of distributed antenna systems (DAS). The objective of the optimization is to find the number of deployed antennas, their optimal locations and the power transmitted from each antenna. The optimal configuration should minimize the deployment cost, maximize wireless coverage while minimizing power leakage outside a building. One of the main challenges in this problem is that in DAS all antennas are fed from the same base station. This means that the total power transmitted is constant and hence increasing the power assigned to one antenna would require decreasing the power on all other antennas. Similarly adding an antenna would require decreasing the power assigned to existing antennas. Previous approaches simplified the problem by assuming equal transmitted power from all antennas in the DAS, and they ignored the fact that the sum of these powers should remain constant. This paper provides a new multi-objective formulation for indoor DAS planning that considers a fixed total transmitted power constraint. The paper proposes a solution method that uses simulated annealing with smart neighborhood search steps to reach a near optimal solution. Results showed that the proposed formulation obtained better indoor DAS configuration and that including antenna power in the optimization provided a solution that contain less antennas and better average power compared to the equal power configuration.

Delay-margin based traffic engineering for MPLS-DiffServ networks

This paper presents a delay-margin based traffic engineering (TE) approach to provide end-to-end quality of service (QoS) in multi-protocol label switching (MPLS) networks using differentiated services (DiffServ) at the link level. The TE, including delay, class, and route assignments, is formulated as a nonlinear optimization problem reflecting the inter-class and inter-link dependency introduced by DiffServ and end-to-end QoS requirements. Three algorithms are used to provide a solution to the problem: The first two, centralized offline route configuration and link-class delay assignment, operate in the convex areas of the feasible region to consecutively reduce the objective function using a per-link per-class decomposition of the objective function gradient. The third one is a heuristic that promotes/demotes connections at different links in order to deal with concave areas that may be produced by a trunk route usage of more than one class on a given link. Approximations of the three algorithms suitable for on-line distributed TE operation are also derived. Simulation is used to show that proposed approach can increase the number of users while maintaining end-to-end QoS requirements.

Scheduling algorithms in mobile WiMAX for rtPS QoS class

This paper proposes a scheduling approach for mobile uplink WiMAX system that provides a trade-off between delay requirement satisfaction and throughput maximization. The paper starts by introducing three scheduling algorithms each with a different objective. The first aim is to maximize the throughput of the system, while maintaining the user fairness. The second aim is to satisfy the delay requirements and the third focuses mainly on user fairness while maintaining an acceptable delay. These three uplink scheduling algorithms are based on an Alternative Factor parameter that selects the best channel of each user for the system throughput maximization while providing the fairness among users. The trade-off proposed in this paper is achieved using Alternative Factor with Mix of SNR and Queue Aware (AFMSQA) scheduling algorithm. AFMSQA combines the features of these three algorithms. The paper uses NS2 to analyze the three algorithms and to compare them to the new proposed AFMSQA approach. The results show that AFMSQA provides the transaction between high throughput performance and good delay results.

An enhanced preprocessing dependent image theory algorithm for indoor coverage solutions

Hot spot coverage requirements of indoor environments necessitate adequate network platforms and optimal network planning. Optimal network planning imposes successive iterative computations and evaluations of network coverage until the best antenna layout is attained. Accordingly, accurate and scalable indoor propagation models become of the ultimate essence. In this paper, an efficient methodology for feasible reflection region assessment is developed to enhance a recently proposed preprocessing dependent image theory based ray tracing algorithm. The feasible reflection region depicts reception point grids of the indoor layout under study that fall within the foot print of a given transmitter image. The methodology proposed in this paper utilizes the intersection points between the stored preprocessing bounds of the feasible reflection region with lines that are drawn parallel to the walls of the indoor layout to achieve significant computational enhancements in the feasible reflection region assessment phase of the indoor coverage computations. The proposed enhanced ray tracing algorithm is tested in different indoor configurations. Simulation results confirm the major computational gain attained through the proposed enhancements while maintaining computational accuracy.

On the impact of RN16 decoding errors on time throughput of RFID systems

UHF EPC Gen2 RFID systems use Dynamic Frame Slotted ALOHA (DFSA) to manage reading of multiple RFID tags. In DFSA, the reader may receive short address messages (RN16) from one or more tags at any given timeslot. To enable RFID readers to read a significantly large population of tags within a small time interval, it is required to increase the underlying throughput by maximizing the percentage of timeslots in which the reader may receive RN16 messages correctly. Common convention in the literature presumes that readers have the ability to correctly decode all RN16 messages from single-tag timeslots as well as to resolve at least one RN16 message from two-tag collision timeslots. However, practically dependent on operating SNR conditions, the reader may incur RN16 decoding errors within such timeslots. As a result, attainable throughputs become inferior to theoretical limits expected in the corresponding literature. This paper analyzes the time throughput performance of RFID systems with imperfect RN16 decoding. The optimal DFSA frame length is derived and the corresponding throughput performance is evaluated. Results reveal that there exists a cutoff probability when the reader should stop attempting to resolve two-tag collisions and only confine its efforts in decoding single-tag timeslots.

Downlink capacity evaluation for indoor DAS in LTE networks

Providing high-performance indoor coverage, especially with continuous growth in high data rate demands, is a considerable challenge. This constitutes a major problem given that statistics indicate that 80% of data is expected to be generated from within indoor environments. Therefore, in order to achieve the objectives of LTE cellular systems in terms of reliable broadband communications, careful research has been taken into providing solutions for indoor communications. One of these solutions is the distributed antenna system (DAS). In DAS, a network of antennas is used to provide coverage within a given floor of a certain building. Consequently, multiple antennas within a given floor are expected to provide a better chance for line-of-site situations, the matter which improves the overall signal quality. In this paper, downlink capacity evaluation for an indoor distributed antenna system is performed. The aim is to find the optimum number of antennas that should be deployed in a specific system to optimize the use of available resources. The main target is to find efficient approximation models and to validate their level of accuracy through comparing them to the actual simulation. Different indoor propagation models are used in this paper to verify the validity of the proposed approaches and they all take into account the environment of the studied indoor area.