11,620 research outputs found

    Optimal channel allocation with dynamic power control in cellular networks

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    Techniques for channel allocation in cellular networks have been an area of intense research interest for many years. An efficient channel allocation scheme can significantly reduce call-blocking and calldropping probabilities. Another important issue is to effectively manage the power requirements for communication. An efficient power control strategy leads to reduced power consumption and improved signal quality. In this paper, we present a novel integer linear program (ILP) formulation that jointly optimizes channel allocation and power control for incoming calls, based on the carrier-to-interference ratio (CIR). In our approach we use a hybrid channel assignment scheme, where an incoming call is admitted only if a suitable channel is found such that the CIR of all ongoing calls on that channel, as well as that of the new call, will be above a specified value. Our formulation also guarantees that the overall power requirement for the selected channel will be minimized as much as possible and that no ongoing calls will be dropped as a result of admitting the new call. We have run simulations on a benchmark 49 cell environment with 70 channels to investigate the effect of different parameters such as the desired CIR. The results indicate that our approach leads to significant improvements over existing techniques.Comment: 11 page

    Applications of Soft Computing in Mobile and Wireless Communications

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    Soft computing is a synergistic combination of artificial intelligence methodologies to model and solve real world problems that are either impossible or too difficult to model mathematically. Furthermore, the use of conventional modeling techniques demands rigor, precision and certainty, which carry computational cost. On the other hand, soft computing utilizes computation, reasoning and inference to reduce computational cost by exploiting tolerance for imprecision, uncertainty, partial truth and approximation. In addition to computational cost savings, soft computing is an excellent platform for autonomic computing, owing to its roots in artificial intelligence. Wireless communication networks are associated with much uncertainty and imprecision due to a number of stochastic processes such as escalating number of access points, constantly changing propagation channels, sudden variations in network load and random mobility of users. This reality has fuelled numerous applications of soft computing techniques in mobile and wireless communications. This paper reviews various applications of the core soft computing methodologies in mobile and wireless communications

    Improving Link Reliability through Network Coding in Cooperative Cellular Networks

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    The paper proposes a XOR-based network coded cooperation protocol for the uplink transmission of relay assisted cellular networks and an algorithm for selection and assignment of the relay nodes. The performances of the cooperation protocol are expressed in terms of network decoder outage probability and Block Error Rate of the cooperating users. These performance indicators are analyzed theoretically and by computer simulations. The relay nodes assignment is based on the optimization, according to several criteria, of the graph that describes the cooperation cluster formed after an initial selection of the relay nodes. The graph optimization is performed using Genetic Algorithms adapted to the topology of the cooperation cluster and the optimization criteria considered

    A simulation-based algorithm for solving the resource-assignment problem in satellite telecommunication networks

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    This paper proposes an heuristic for the scheduling of capacity requests and the periodic assignment of radio resources in geostationary (GEO) satellite networks with star topology, using the Demand Assigned Multiple Access (DAMA) protocol in the link layer, and Multi-Frequency Time Division Multiple Access (MF-TDMA) and Adaptive Coding and Modulation (ACM) in the physical layer.En este trabajo se propone una heurística para la programación de las solicitudes de capacidad y la asignación periódica de los recursos de radio en las redes de satélites geoestacionarios (GEO) con topología en estrella, con la demanda de acceso múltiple de asignación (DAMA) de protocolo en la capa de enlace, y el Multi-Frequency Time Division (Acceso múltiple por MF-TDMA) y codificación y modulación Adaptable (ACM) en la capa física.En aquest treball es proposa una heurística per a la programació de les sol·licituds de capacitat i l'assignació periòdica dels recursos de ràdio en les xarxes de satèl·lits geoestacionaris (GEO) amb topologia en estrella, amb la demanda d'accés múltiple d'assignació (DAMA) de protocol en la capa d'enllaç, i el Multi-Frequency Time Division (Accés múltiple per MF-TDMA) i codificació i modulació Adaptable (ACM) a la capa física

    Optimisation of Mobile Communication Networks - OMCO NET

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    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

    GA and ACO Algorithms Applied to Optimizing Location of Controllers in Wireless Networks

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    Optimizing location of controllers in wireless networks is an important problem in the cellular mobile networks designing. In this paper, I present two algorithms based on Genetic Algorithm (GA) and Ant Colony Optimization (ACO) to solve it. In the first algorithm, my objective function is determined by the total distance based on finding maximum flow in a bipartite graph using Ford-Fulkerson algorithm. In the second algorithm, I generate pheromone matrix of ants and calculate the pheromone content of the path from controller i to base station j using the neighborhood includes only locations that have not been visited by ant k when it is at controller i. At each step of iterations, I choose good solutions satisfying capacity constraints and update step by step to find the best solution depending on my cost functions. I evaluate the performance of my algorithms to optimize location of controllers in wireless networks by comparing to SA, SA-Greedy, LB-Greedy algorithm. Numerical results show that my algorithms proposed have achieved much better more than other algorithms.DOI:http://dx.doi.org/10.11591/ijece.v3i2.229

    The cavity approach for Steiner trees packing problems

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    The Belief Propagation approximation, or cavity method, has been recently applied to several combinatorial optimization problems in its zero-temperature implementation, the max-sum algorithm. In particular, recent developments to solve the edge-disjoint paths problem and the prize-collecting Steiner tree problem on graphs have shown remarkable results for several classes of graphs and for benchmark instances. Here we propose a generalization of these techniques for two variants of the Steiner trees packing problem where multiple "interacting" trees have to be sought within a given graph. Depending on the interaction among trees we distinguish the vertex-disjoint Steiner trees problem, where trees cannot share nodes, from the edge-disjoint Steiner trees problem, where edges cannot be shared by trees but nodes can be members of multiple trees. Several practical problems of huge interest in network design can be mapped into these two variants, for instance, the physical design of Very Large Scale Integration (VLSI) chips. The formalism described here relies on two components edge-variables that allows us to formulate a massage-passing algorithm for the V-DStP and two algorithms for the E-DStP differing in the scaling of the computational time with respect to some relevant parameters. We will show that one of the two formalisms used for the edge-disjoint variant allow us to map the max-sum update equations into a weighted maximum matching problem over proper bipartite graphs. We developed a heuristic procedure based on the max-sum equations that shows excellent performance in synthetic networks (in particular outperforming standard multi-step greedy procedures by large margins) and on large benchmark instances of VLSI for which the optimal solution is known, on which the algorithm found the optimum in two cases and the gap to optimality was never larger than 4 %

    Optimization Framework and Graph-Based Approach for Relay-Assisted Bidirectional OFDMA Cellular Networks

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    This paper considers a relay-assisted bidirectional cellular network where the base station (BS) communicates with each mobile station (MS) using OFDMA for both uplink and downlink. The goal is to improve the overall system performance by exploring the full potential of the network in various dimensions including user, subcarrier, relay, and bidirectional traffic. In this work, we first introduce a novel three-time-slot time-division duplexing (TDD) transmission protocol. This protocol unifies direct transmission, one-way relaying and network-coded two-way relaying between the BS and each MS. Using the proposed three-time-slot TDD protocol, we then propose an optimization framework for resource allocation to achieve the following gains: cooperative diversity (via relay selection), network coding gain (via bidirectional transmission mode selection), and multiuser diversity (via subcarrier assignment). We formulate the problem as a combinatorial optimization problem, which is NP-complete. To make it more tractable, we adopt a graph-based approach. We first establish the equivalence between the original problem and a maximum weighted clique problem in graph theory. A metaheuristic algorithm based on any colony optimization (ACO) is then employed to find the solution in polynomial time. Simulation results demonstrate that the proposed protocol together with the ACO algorithm significantly enhances the system total throughput.Comment: 27 pages, 8 figures, 2 table
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