A comprehensive review of methods for the channel allocation problem (original) (raw)
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Application of an Optimization Algorithm for Channel Assignment in Mobile Communication
The channel assignment problem is a complex problem where a minimum number of channels have to be assigned, under several constraints, to the calls requested in the cellular system. Several approaches have been proposed to solve the dynamic channel assignment (DCA). In this paper, DCA has been modeled as a combinatorial optimization problem. Genetic Algorithm (GA) is a simple tool that can be used to solve such optimization problems in a fast and effective manner. It selects the best option from all the possible solutions, thus making it very different from all the other existing approaches. Several constraints like cochannel and adjacent channel interferences have been considered while solving the channel assignment problem. The performance of the proposed GA-DCA model has been evaluated by a computer simulation tool under the effective of varying cellular capacity.
Principles of Wireless Communications Books
Scholars-Press Publication
In this book deals with the fundamental cellular radio concepts such as frequency reuse and handoff. This also demonstrates the principle of trunking efficiency and how trunking and interference issues between mobile and base stations combine to affect the overall capacity of cellular systems. It presents different ways to radio propagation models and predict the large scale effects of radio propagation. This also covers small propagation effects such as fading, time delay spread and Doppler spread and describes how to measures signal bandwidth. The objective of the student should be made to know the characteristic of wireless channel, learn the various cellular architectures, understand the concepts behind various digital signalling schemes for fading channels and also be familiar the various multipath mitigation techniques and multiple antenna systems. The outcomes of the course, the student should be able to characterize wireless channels, design and implement various signalling schemes for fading channels, design a cellular system, compare multipath mitigation techniques and analyze their performance, design with transmit/receive diversity and MIMO systems.
Comparative Analysis of Simulated Annealingand Tabu Search Channel Allocation Algorithms
International Journal of Computer Theory and Engineering, 2009
The major aim of the Frequency Allocation Problem in mobile radio networks is to allocate a limited number of frequencies to all radio cells in a network while minimizing electromagnetic interference due to the re-use of frequencies. This problem is identified as NP-hard, and of huge significance in practice since enhanced solutions will permit a telecommunications operator to administer bigger cellular networks. This paper presents and implements two algorithms tabu search and simulated annealing. The algorithms are tested on realistic and large problem instances and compared. Results of comparison show that the tabu search is less efficient than simulated annealing algorithm.
Channel Assignment Optimisation Using an Adaptive Heuristic
2003
Abstract: The rapid development of mobile communications has caused a higher demand of radio channel or carrier frequency due to additional mobile subscribers. With a limited frequency bandwidth allocated to mobile operators, good network planning is important to avoid congestion in the network. Some of the methods used to improve congestion in mobile networks is cell splitting and frequency reuse, but without good planning, such as assignment of frequencies to base station and coverage area, it will result in extra costs to ...
An Estimation of Distribution Algorithm for the Channel Assignment Problem
The channel assignment problem in cellular radio networks is known to belong to the class of NP-complete optimisation problems. In this paper we present a new algorithm to solve the Channel Assignment Problem using Estimation of Distribution Algorithm. The convergence rate of this new method is shown to be very much faster than other methods such as simulated annealing, neural networks and genetic algorithm.
Survey on Optimization Techniques used for Resource Allocation in Wireless Communication System
In recent years telecommunication is playing a major role in the field of communication. In wireless communication systems, the necessity to provide more number of users with high-rate communication links leads to optimization problems. Demands of resource block assignment, interference and power consumption at base station and mobile devices have to be answered in the face of time-varying frequency-selective channels. In addition, the heterogeneity of recent mobile services means that delay and data rate requirements vary significantly between applications and users. These requirements are summarized as resource allocation problems.
Heuristics for optimizing minimum interference channel allocation problem in cellular networks
Journal of integrated science and technology, 2024
The channel allocation problem (CAP) requires cellular communication services to meet electromagnetic constraints, such as having the least bandwidth, satisfy customer demand/capacity, less call-blocking probability, and the least level of interference. With a limited bandwidth and cumulative growth in non-uniform dynamic demand which varies depending on the times of day, the problem of channel allocation becomes more crucial. Artificial intelligence Technique for heuristic optimization can be used to minimize the overall interference level (MICAP) and satisfy the channel demand. The MICAP is solved using the Genetic Algorithm and Simulated Annealing. When designing the cost or fitness function, cochannel, and co-site channel constraints are taken into account. The channel allocation matrix is observed, the cost function value is measured for the number of iterations or generations needed to satisfy the demand with constraints imposed. When the simulated observations are compared to previously reported results, the cost function value is found to be reduced for the benchmarks EX1, HEX1, HEX2, HEX3, HEX4, P1, P2, and P3, each of which indicates a distinct number of cells, frequency, and traffic demand.
2018
With the rapid growth of mobile communications, solving the channel assignment problem has now become a new challenge in research. In this paper, we present an efficient technique for solving the Channel Assignment Problem (CAP). We first map a given CAP, P, to a smaller subset P of cells of the network, which actually reduces the search space. This reduction is done using a multi-colouring method. Then the tabu search algorithm is applied to solve the new problem P. This method reduces the computing time drastically. The latter is then used to solve the original problem by using a modified forced assignment with rearrangement (FAR) operation. The proposed method has been tested on well known benchmark problems. Optimal solutions have been obtained with zero blocked calls for all the cases with improved computation time. Furthermore, there are many unused frequencies which can be used for changes in demands.
Channel allocation scheme for cellular networks using evolutionary computing
International Journal of Artificial Intelligence and Soft Computing, 2014
The usage of mobile communications systems has grown exponentially. But, the bandwidth available for mobile communications is finite. Hence, there is a desperate attempt to optimise the channel assignment schemes. In this work, some of the quality of service parameters such as residual bandwidth, number of users, duration of calls, frequency of calls, priority, time of calls and mean opinion score are considered. Genetic algorithm and artificial neural networks is used to determine the optimal channel assignment considering the quality of service parameters. The simulation results show that genetic algorithm performs better than frequency assignment at random, a heuristic method. But application of artificial neural networks outperforms genetic algorithm and frequency assignment at random method by a considerable margin. Channel allocation can be optimised using these soft computing techniques resulting in better throughput.