System level performance of ATM transmission over a DS-CDMA satellite link.

PhDAbstract not availableEuropean Space Agenc

System modeling and performance evaluation of rate allocation schemes for packet data services in wideband CDMA systems

To fully exploit the potential of a wideband CDMA-based mobile Internet computing system, an efficient algorithm is needed for judiciously performing rate allocation, so as to orchestrate and allocate bandwidth for voice services and high data rate applications. However, in existing standards (e.g., cdma2000), only a first-come-first-served equal sharing allocation algorithm is used, potentially leading to a low bandwidth utilization and inadequate support of high data rate multimedia mobile applications (e.g., video/audio files swapping, multimedia messaging services, etc.). In this paper, we first analytically model the rate allocation problem that captures realistic system constraints such as downlink power limits and control, uplink Interference effects, physical channel adaptation, and soft handoff. We then suggest six efficient rate allocation schemes that are designed based on different philosophies: rate optimal, fairness-based, and user-oriented. Simulations are performed to evaluate the effectiveness of the rate allocation schemes using realistic system parameters In our model.published_or_final_versio

Modified bipartite matching for multiobjective optimization: Application to antenna assignments in MIMO systems

Based on the Hungarian algorithm, the Kuhn-Munkres algorithm can provide the maximum weight bipartite matching for assignment problems. However, it can only solve the single objective optimization problem. In this paper, we formulate the multi-objective optimization (MO) problem for bipartite matching, and propose a modified bipartite matching (MBM) algorithm to approach the Pareto set with a low computational complexity and to dynamically select proper solutions with given constraints among the reduced matching set. In addition, our MBM algorithm is extended to the case of asymmetric bipartite graphs. Finally, we illustrate the application of MBM to antenna assignments in wireless multiple-input multiple-output (MIMO) systems for both symmetric and asymmetric scenarios, where we consider the multi-objective optimization problem with the maximization of the system capacity, total traffic priority, and long-term fairness among all mobile users. The simulation results show that MBM can effectively reduce the matching set and dynamically provide the optimized performance with different quality of service (QoS) requirements. © 2006 IEEE.published_or_final_versio

Optimisation of Mobile Communication Networks - OMCO NET

The mini conference “Optimisation of Mobile Communication Networks” focuses on advanced methods for search and optimisation applied to wireless communication networks. It is sponsored by Research & Enterprise Fund Southampton Solent University. The conference strives to widen knowledge on advanced search methods capable of optimisation of wireless communications networks. The aim is to provide a forum for exchange of recent knowledge, new ideas and trends in this progressive and challenging area. The conference will popularise new successful approaches on resolving hard tasks such as minimisation of transmit power, cooperative and optimal routing

Random Neural Networks and Optimisation

In this thesis we introduce new models and learning algorithms for the Random Neural Network (RNN), and we develop RNN-based and other approaches for the solution of emergency management optimisation problems. With respect to RNN developments, two novel supervised learning algorithms are proposed. The first, is a gradient descent algorithm for an RNN extension model that we have introduced, the RNN with synchronised interactions (RNNSI), which was inspired from the synchronised firing activity observed in brain neural circuits. The second algorithm is based on modelling the signal-flow equations in RNN as a nonnegative least squares (NNLS) problem. NNLS is solved using a limited-memory quasi-Newton algorithm specifically designed for the RNN case. Regarding the investigation of emergency management optimisation problems, we examine combinatorial assignment problems that require fast, distributed and close to optimal solution, under information uncertainty. We consider three different problems with the above characteristics associated with the assignment of emergency units to incidents with injured civilians (AEUI), the assignment of assets to tasks under execution uncertainty (ATAU), and the deployment of a robotic network to establish communication with trapped civilians (DRNCTC). AEUI is solved by training an RNN tool with instances of the optimisation problem and then using the trained RNN for decision making; training is achieved using the developed learning algorithms. For the solution of ATAU problem, we introduce two different approaches. The first is based on mapping parameters of the optimisation problem to RNN parameters, and the second on solving a sequence of minimum cost flow problems on appropriately constructed networks with estimated arc costs. For the exact solution of DRNCTC problem, we develop a mixed-integer linear programming formulation, which is based on network flows. Finally, we design and implement distributed heuristic algorithms for the deployment of robots when the civilian locations are known or uncertain

Performance analysis of the interference adaptation dynamic channel allocation technique in wireless communication networks

Dynamic channel allocation (DCA) problem is one of the major research topics in the wireless networking area. The purpose of this technique is to relieve the contradiction between the increasing traffic load in wireless networks and the limited bandwidth resource across the air interface. The challenge of this problem comes from the following facts: a) even the basic DCA problem is shown to be NP-complete (none polynomial complete); b) the size of the state space of the problem is very large; and c) any practical DCA algorithm should run in real-time. Many heuristic DCA schemes have been proposed in the literature. It has been shown through simulation results that the interference adaptive dynamic channel allocation (IA-DCA) scheme is a promising strategy in Time Devision [sic] Multiple Accesss/Frequency Devision [sic] Multiple Accesss [sic] (TDMA/FDMA) based wireless communication systems. However, the analytical work on the IA-DCA strategy in the literature is nearly blank. The performance of a, DCA algorithm in TDMA/FDMA wireless systems is influenced by three factors: representation of the interference, traffic fluctuation, and the processing power of the algorithm. The major obstacle in analyzing IA-DCA is the computation of co-channel interference without the constraint of conventional channel reuse factors. To overcome this difficulty, one needs a representation pattern which can approximate the real interference distribution as accurately as desired, and is also computationally viable. For this purpose, a concept called channel reuse zone (CRZ) is introduced and the methodology of computing the area of a CRZ with an arbitrary, non-trivial channel reuse factor is defined. Based on this new concept, the computation of both downlink and uplink CO-channel interference is investigated with two different propagation models, namely a simplified deterministic model and a shadowing model. For the factor of the processing power, we proposed an idealized Interference Adaptation Maximum Packing (IAMP) scheme, which gives the upper bound of all IA-DCA schemes in terms of the system capacity. The effect of traffic dynamics is delt [sic] with in two steps. First, an asymptotic performance bound for the IA-DCA strategy is derived with the assumption of an arbitrarily large number of channels in the system. Then the performance bound for real wireless systems with the IA-DCA strategy is derived by alleviating this assumption. Our analytical result is compared with the performance bound drawn by Zander and Eriksson for reuse-partitioning DCA1 and some simulation results for IA-DCA in the literature. It turns out that the performance bound obtained in this work is much tighter than Zander and Eriksson\u27s bound and is in agreement with simulation results. 1only available for deterministic propagation model and downlink connection