Channel Assignment In Cellular Networks Research Articles

Irregular Cellular Learning Automata.

Cellular learning automaton (CLA) is a recently introduced model that combines cellular automaton (CA) and learning automaton (LA). The basic idea of CLA is to use LA to adjust the state transition probability of stochastic CA. This model has been used to solve problems in areas such as channel assignment in cellular networks, call admission control, image processing, and very large scale integration placement. In this paper, an extension of CLA called irregular CLA (ICLA) is introduced. This extension is obtained by removing the structure regularity assumption in CLA. Irregularity in the structure of ICLA is needed in some applications, such as computer networks, web mining, and grid computing. The concept of expediency has been introduced for ICLA and then, conditions under which an ICLA becomes expedient are analytically found.

A NEW DYNAMIC SINGLE-ROW ROUTING FOR CHANNEL ASSIGNMENTS

One of the graph theoretic approaches of channel assignment for cellular networks is routing a pair of nodes arranged in a single-row axis called single-row routing problem. The network with nodes representing caller and receiver is to be transformed into a single-row network efficiently is proposed. The connected graph derived from the base network is presented using incidence matrix. The rows and columns of the matrix represent the ordered list of zones and ordered list of nets respectively for the Singlerow network. By successive row-interchange of the matrix, maximum number of nodes adjacent to each other can be placed with minimum distance. The proposed method with the support of ESSR bySalleh in [2], only increases the speed of convergence to the optimal ordering of nets but also find the minimum value of energy function, street congestion and the number of doglegs. The comparative analysis between the traditional method and the proposed method is also discussed.

Fragile Bin-packing Problem with Start-Up Weight for Channel Assignment in Cellular Networks

Fragile Bin-packing Problem with Start-Up Weight for Channel Assignment in Cellular Networks

A column generation and branch-and-cut algorithm for the channel assignment problem

We present an exact algorithm for solving the channel assignment problem in cellular telephony networks. This problem consists of assigning sets of channels to the network cells in such a way that the channel demand is satisfied, while avoiding co-channel interference and adjacent channel interference and respecting the channel spacing constraint for each antenna. In a previous article [Jaumard B, Marcotte O, Meyer C, Vovor T. Comparison of column generation models for channel assignment in cellular networks. Discrete Applied Mathematics 2002; 118:299–322], we formulated this problem as a covering problem in two different ways and compared these two formulations and another formulation both from a theoretical and computational point of view (by solving their linear relaxations). In the present article we focus on the best set covering formulation, where the subsets are sets of cells that can be assigned the same channel, and we actually solve two versions of the integer program. In the first version, we seek to minimize the unmet demand, while in the second, we seek to minimize the overall interference while assigning the required number of channels to each cell. In either version, the integer program is solved by an algorithm combining the column generation technique and a branch-and-cut scheme. Finally, we present the solutions produced by these algorithms for some instances of European networks and real-life instances supplied by the Bell Mobilité company.

Channel Assignment for Cellular Networks Based on a Local Modified Hopfield Neural Network

In this paper, we propose a modified discrete Hopfield neural networks algorithm for the channel assignment problem. In opposition to previous work, we tried to apply the optimization locally on a per cell basis in order to reduce the CPU processing time and decrease the designed system complexity while obtaining a near-optimum solution. In addition, the research is extended to study the algorithm performance in a more realistic cellular system where the number of requested channels is continuously changing with time. In this paper, the channel assignment problem is formulated as an energy function which is at its minimum when all the defined compatibility constraints are satisfied and the assigned channel number (ACN) is equal to the requested channel number (RCN) in each cell.

Worst-case analysis of a dynamic channel assignment strategy

We consider the problem of channel assignment in cellular networks with arbitrary reuse distance. We show upper and lower bounds for the competitive ratio of a previously proposed and widely studied version of dynamic channel assignment, which we refer to as the greedy algorithm. We study two versions of this algorithm: one that performs reassignment of channels, and one that never reassigns channels to calls. For reuse distance 2, we show tight bounds on the competitive ratio of both versions of the algorithm. For reuse distance 3, we show non-trivial lower bounds for both versions of the algorithm.

Comparison of column generation models for channel assignment in cellular networks

We study several formulations of the channel assignment problem in an FDMA network as a linear integer 0–1 program. We consider the objective of minimizing the unsatisfied channel demand while satisfying the co-channel, the adjacent channel and the antenna channel spacing constraints. We compare the formulations according to two criteria: the ease with which their linear programming relaxations can be solved, and the quality of the bounds provided by these relaxations. We show that the best lower bound is provided by one of the set covering formulations, while the other two formulations provide the same lower bound. We present computational results that support the theoretical comparison of the models.

A graph theoretic approach for channel assignment in cellular networks

We define a cellular assignment graph to model the channel assignment problem in a cellular network where overlapping cell segments are included in the model. Our main result is the Capacity-Demand Theorem which shows a channel assignment function is always possible unless there is a connected subregion of cells and overlap segments containing more channel requests then the total capacity of all transceivers within or on the boundary of the subregion and covering any part of the subregion with an overlapping segment. We further describe the simplicity and regularity of our proposed cellular assignment graphs and their accessibility for simulation and theoretical investigation without artifacts from the overall geographical region boundaries.

Maximum packing channel assignment in cellular networks

We study the performance of the maximum packing channel assignment algorithm (MPA) in channelized cellular networks. MPA is a greedy algorithm, which rejects a call only when it is forced to do so, even if this involves rearrangement of channels assigned to the ongoing calls, without dropping any of them. We ignore handoffs and model the channel reuse constraints in the cellular network by a hypergraph. As the traffic and the number of channels are scaled together, we get a limiting regime where the blocking probability in the cells can be computed by solving a nonlinear optimization problem. The carried traffic in this limiting case is an upper bound on the performance of MPA for practical finite-channel systems. We show that the performance of MPA in a finite-channel cellular system can be closely approximated by considering a simple fixed-routing circuit-switched network. Thus, the finite-channel performance of MPA can be studied using methods well known in the area of circuit-switched networks. We compare the performance of MPA with other asymptotically optimal algorithms and demonstrate its optimality for low and moderate offered traffic. We envisage MPA as a practical channel assignment algorithm, for moderate size systems, and suggest approximations to reduce its complexity.

Threshold priority policy for channel assignment in cellular networks

This paper presents a new policy called the threshold priority policy (TPP) for assigning channels in cellular networks. The performance of TPP is compared with the performance of the well-known cutoff priority policy (CPP) and the nonprioritized complete sharing policy (CSP). Several numerical experiments are done for various values of offered load and portable mobility. The results are compared using three unified performance metrics which take into account the trade-off between new call blocking probability and the forced termination probability.

Optimal channel assignment in cellular networks

AbstractIn this paper, we consider the problem of assigning frequencies to mobile terminals in a cellular network. We show that an optimal solution can be obtained by solving a sequence of alternating linear and quadratic maximization programming problems. We address co‐channel constraints and adopt as an objective function the maximization of potentially established calls. Our algorithm is fairly general, and does not depend on any special network structure. This study indicates that mathematical programming can be used as an efficient technique for solving the aforementioned problem.