Channel Allocation In Cellular Networks Research Articles

Bio-inspired power control and channel allocation for cellular networks with D2D communications

With the tremendous increment of traffic in the next generation mobile networks, device to device (D2D) communication is proposed to relieve the traffic burden of the base station and improve the overall network capacity. It supports direct communications between devices and could reuse the resources of cellular users (CUs). Despite the advantages, D2D communications bring great challenges in interference management. In this paper, we study the power control and channel allocation problems in three scenarios: (1) one CU and one D2D pair; (2) one CU and multiple D2D pairs; (3) multiple CUs and multiple D2D pairs. The goal is to coordinate the mutual interferences and maximize the overall network capacity. We derive sufficient conditions to guarantee the efficiency of D2D communications in scenarios with one CU and one D2D pair. We propose the bio-inspired PSO-P power control algorithm for the scenarios with one CU and multiple D2D pairs, and the PSO-CP algorithm for the scenarios with multiple CUs and multiple D2D pairs to jointly assign channels and powers. Simulation results show that the proposed algorithms are efficient in improving the overall network capacity.

Analysis of channel allocation and management using tlbo, ga & de algorithms in cellular networks

Accuracy of spectrum sensing in cellular mobile networks can be increased by reducing the sensing error probability, call blocking probability & by increasing network throughput. In our Project work, an advanced algorithms like Teaching Learning Based Optimization (TLBO), Genetic (GA) and Differential Evaluation (DE) Algorithms are used to analyze the sensing error probability, call blocking probability and network throughput. We will propose a channel allocation and management scheme with the above mentioned algorithms for supporting mobile users. With the help of these algorithms, sensing error and call blocking probabilities are analyzed to find out an optimal value for reducing the errors to some extent and improving network throughput. Channel Allocation in cellular networks is a key aspect with channel impairments and non-ideal antenna patterns. Finally, performance analysis is done through comparison of simulation results.

Hybrid channel allocation in cellular network based on genetic algorithm and particle swarm optimisation methods

The challenge in wireless cellular network is to suit the changeable traffic demand by assigning appropriate channels from limited frequency spectrum and to maintain a desirable stratum of interference level. The system capacity can be improved by a reduction in interference effect by applying effectual channel assignment technique. This work proposes, genetic algorithm (GA) and particle swarm optimisation (PSO) techniques, with hybrid channel allocation for interference reduction. In GA, integer genetic representation for crossover and mutation operation is applied and graph theory based fitness function is designed. In PSO, hard and soft constraints are used for designing fitness function. The proposed GA and PSO compute co-channel and co-site interferences represented by interfering edges, the computation time and generations/iterations required. The signal-to-interference ratio (SIR) is determined, considering attenuation of the signal predicted by applying Hata propagation model. The performances of the proposed methods are applied on benchmark instances and are compared with the reported literature. The proposed PSO shows improvement in performance than GA in terms of reduction in interference, required computation time, generations/iterations required also improvement in the SIR.

Joint user scheduling and channel allocation for cellular networks with full duplex base stations

Full-duplex communication (FDC) can potentially double the network capacity by allowing a device to transmit and receive simultaneously on the same frequency band. In this study, a novel resource allocation and user scheduling algorithm is proposed to maximise the network throughput for a cellular network with full-duplex (FD) base stations (BSs). The authors consider that FDC is utilised at the BS with imperfect self-interference (SI) cancellation while user devices only work in the traditional half-duplex (HD) way. In addition, to potentially cancel co-channel interference caused by other users, the opportunistic interference cancellation (OIC) technique is applied at user side. Since FDC does not always perform better than HD due to residual SI (RSI), a joint mode selection, user scheduling, and channel allocation problem is formulated to maximise the system throughput. The optimisation problem is non-convex and NP-hard, thereby a suboptimal heuristic algorithm with low computational complexity is proposed. Numerical results demonstrate that user diversity gain, FD gain, and OIC gain can be achieved by the proposed algorithm, respectively. The performance of FDC depends on the intensity of RSI and the distribution of user devices.

An optimization technique for efficient channel allocation in cellular network

For today’s wireless mobile communication systems, efficient use of limited radio spectrum with minimum interferences is required. Itinvestigates an Optimal Genetic Algorithm approach (GA) for Hybrid Channel allocation (NP hard) focusing on reduction in interference in cellular Network. Obtained an interference graph based fitness function to enhance the performance of HCA for interference reduction. It is shown that the use of integer genetic representation for Crossover and mutation operation enhances the speed of GA leading to less computation time. Comparison of proposed method is done with reported literature for KUNZ 4 which results in less co-channel and co-site interference depicted by interfering edges and also number of generations required are less. The result for KUNZ 1, KUNZ 2 and KUNZ 3 are obtained with minimum interference along with computation time.

Agent-based energy constrained channel allocation in mobile computing using GA

Energy is a significant limitation on mobile devices as battery power often drains very fast during execution. Little attention has been paid to the optimal power consumption by software execution on these mobile devices. Cellular systems are usually powered by battery, and therefore power conservation is a major concern in such networks. Energy-efficient algorithms serve better to save power in such environments. Optimal uses of the network resources may lead to power conservation in such systems. In this paper, an energy-efficient resources management algorithm to profile power consumption is proposed. Power consumption of the system is described with respect to certain workload. The proposed power management solution uses mobile agent technology for energy-efficient channel allocation in cellular networks. To handle this, a meta-heuristics technique, Genetic Algorithm, is used as the problem is combinatorial complex. Extensive simulation study, to evaluate the performance, exhibits the veracity of the proposed model.

Optimal Channel Allocation with Dynamic Power Control in Cellular Networks

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.

Dynamically adaptive channel reservation scheme for cellular networks

In personal communications networks (PCN) supporting network-wide handoffs, new and handoff requests compete for connection resources in both mobile and backbone networks. Forced call terminations due to handoff call blocking are generally more objectionable than new call blocking. In general, most of the previously proposed schemes for radio channel allocation in cellular networks reduce handoff call blocking probability substantially at the expense of increasing the new call blocking probability by giving higher priority to handoff calls over new calls in admission control. This reduces the total admitted traffic and results in inefficient utilization of wireless channels. The tradeoff between the new and handoff calls blocking probabilities should be defined on importance basis. In this paper, we propose a performance metric equation that makes a trade off between the two probabilities depending on the network preferences. Using this equation, we study the performance of various proposed channel reservation schemes. Also in this paper, a new dynamically adaptive channel reservation scheme (DACRS) is developed and compared with other schemes proposed in the literature. The DACRS assigns handoff-reserved channels to new calls depending on the locality principle in which the base station with the help of location estimation algorithms in the mobile location center predicts the position of the mobile terminal. Eventually, the DACRS is designed to improve channel utilization while satisfying the QoS of the calls. As will be shown analytically and through simulation, the DACRS outperforms current reservation schemes and results in more statistical gain, and powerful channel utilization.

NACR: A New Adaptive Channel Reservation in Cellular Communication Systems

Future Personal Communication Networks (PCN) will employ microcells and picocells to support a higher capacity, thus increasing the frequency of handoff calls. Forced call terminations due to handoff call blocking are generally more objectionable than new call blocking. The proposed guard channel schemes for radio channel allocation in cellular networks reduce handoff call blocking probability at the expense of increases in new call blocking probability by giving resource access priority to handoff calls over new calls in call admission control. Under uniform traffic assumptions, it has been shown that a fixed number of guard channels leads to good performance results. In a more realistic system, non-uniform traffic conditions should be considered. In this case, the achieved call blocking probability may deviate significantly from the desired objective. In this paper, we propose a new adaptive guard channel scheme: New Adaptive Channel Reservation (NACR). In NACR, for a given period of time, a given number of channels are guarded in each cell for handoff traffic. An approximate analytical model of NACR is presented. Tabu search method has been implemented in order to optimize the grade of service. Discrete event simulations of NACR were run. The effectiveness of the proposed method is emphasized on a complex configuration.

Distributed fault-tolerant channel allocation for cellular networks

A channel allocation algorithm includes channel acquisition and channel selection algorithms. Most of the previous work concentrates on the channel selection algorithm since early channel acquisition algorithms are centralized and rely on a mobile switching center (MSC) to accomplish channel acquisition. Distributed channel acquisition algorithms have received considerable attention due to their high reliability and scalability. However, in these algorithms, a borrower needs to consult with its interference neighbors in order to borrow a channel. Thus, the borrower fails to borrow channels when it cannot communicate with any interference neighbor. In real-life networks, under heavy traffic load, a cell has a large probability to experience an intermittent network congestion or even a communication link failure. In existing distributed algorithms, since a cell has to consult with a large number of interference neighbors to borrow a channel, the failure rate will be much higher under heavy traffic load. Therefore, previous distributed channel allocation algorithms are not suitable for real-life networks. We first propose a fault-tolerant channel acquisition algorithm which tolerates communication link failures and node (MH or MSS) failures. Then, we present a channel selection algorithm and integrate it into the distributed acquisition algorithm. Detailed simulation experiments are carried out in order to evaluate our proposed methodology. Simulation results show that our algorithm significantly reduces the failure rate under network congestion, communication link failures, and node failures compared to nonfault-tolerant channel allocation algorithms. Moreover, our algorithm has low message overhead compared to known distributed channel allocation algorithms, and outperforms them in terms of failure rate under uniform as well as nonuniform traffic distribution.

Efficient distributed channel allocation for cellular networks

The performance of a distributed dynamic channel allocation algorithm is measured by the call blocking rate, the number of messages exchanged per channel acquisition and the delay incurred in acquiring a channel. In general, there are two approaches in designing distributed channel allocation algorithms: Search and Update. Both of these approaches have advantages and disadvantages. The update approach has shorter acquisition delay and lower call blocking rate, but higher message complexity. On the other hand, the search approach has lower message complexity, but longer acquisition delay and higher call blocking rate. In this paper, we first propose a novel distributed acquisition algorithm, which has similar message complexity as the search approach and similar acquisition delay as the update approach. Then, we present a channel selection algorithm and integrate it into our distributed acquisition algorithm. By a rigorous analysis in terms of delay and message complexity, we show that our channel selection algorithm performs significantly better than the update approach [X. Dong, T.H. Lai, Proceedings of the International Conference on Distributed Computing systems, 1997] and the search approach [R. Prakash, N. Shivaratri, M. Singhal, Proceedings of the 14th ACM Symposium on Principles of Distributed Computing, 1995, pp. 47–56]. Detailed simulation experiments are carried out in order to evaluate our proposed methodology. The performance of our algorithm is compared with those of the Geometric strategy [A. Baiocchi, F.D. Proscoli, F. Grilli, F. Sestini, IEEE Trans. Veh. Technol. February (1995) 14–23], the Search approach [R. Prakash, N. Shivaratri, M. Singhal, Proceedings of the 14th ACM Symposium on Principles of Distributed Computing, 1995, pp. 47–56] and the Update approach [X. Dong, T.H. Lai, Proceedings of the International Conference on Distributed Computing systems, 1997]. Simulation results show that our algorithm outperforms all other approaches in terms of call blocking probability under uniform as well as non-uniform traffic distributions.

Distributed dynamic fault-tolerant channel allocation for cellular networks

Efficient allocation of communication channels is critical for the performance of cellular systems. The centralized channel allocation algorithms proposed in literature are neither robust nor scalable. Several of these algorithms are unable to dynamically adjust to spatial and temporal fluctuations in channel demand (load). We present a distributed dynamic channel allocation (DCA) algorithm in which heavily loaded regions acquire a large number of communication channels, while their lightly loaded neighbors get assigned fewer channels. As the spatial distribution of channel demand changes with time, the spatial distribution of allocated channels adjusts accordingly. The algorithm described in this paper requires minimal involvement of the mobile nodes, thus conserving their limited energy supply. The algorithm is proved to be deadlock free, starvation free, and fair. It prevents cochannel interference and can tolerate the failure of mobile as well as static nodes without any significant degradation in service. Simulation experiments demonstrate that the performance of the proposed distributed dynamic algorithm is comparable to, and for some metrics, better than that of efficient centralized dynamic algorithms where the central switch has complete and latest information about channel availability. The major advantages of the proposed algorithm over its dynamic centralized counterparts are its scalability, flexibility, and low computation and communication overheads.

Adaptive resource allocation for prioritized call admission over an ATM-based wireless PCN

In future personal communications networks (PCNs) supporting network-wide handoffs, new and handoff requests will compete for connection resources in both the mobile and backbone networks. Forced call terminations due to handoff call blocking are generally more objectionable than new call blocking. The previously proposed guard channel scheme for radio channel allocation in cellular networks reduces handoff call blocking probability substantially at the expense of slight increases in new call blocking probability by giving resource access priority to handoff calls over new calls in call admission control. While the effectiveness of a fixed number of guard channels has been demonstrated under stationary traffic conditions, with nonstationary call arrival rates in a practical system, the achieved handoff call blocking probability may deviate significantly from the desired objective. We propose a novel dynamic guard channel scheme which adapts the number of guard channels in each cell according to the current estimate of the handoff call arrival rate derived from the current number of ongoing calls in neighboring cells and the mobility pattern, so as to keep the handoff call blocking probability close to the targeted objective while constraining the new call blocking probability to be below a given level. The proposed scheme is applicable to channel allocation over cellular mobile networks, and is extended to bandwidth allocation over the backbone network to enable a unified approach to prioritized call admission control over the ATM-based PCN.

Design and performance analysis of the algorithms for channel allocation in cellular networks

The authors consider the problem of dynamic channel allocation in cellular networks. Each cell can use any channel, subject to the interference constraints. Channel allocation algorithms are executed by the network switch in a centralized way. The authors show how to design and use objective functions aimed at proper channel allocation and improvement of network performance. As a figure of merit of network performance, they consider the blocking probability in the network as a whole, and the maximum blocking probability in any particular cell of the network ("hot-spot" in the network). They designed three specific channel allocation policies, based on three different objective functions. Compared with two other benchmark policies, the approach shows significant improvement. Performance analysis of various channel allocation policies is virtually impossible without simulations, which are prohibitively time-consuming in the case of small blocking probabilities. The authors propose an original approximate method based on a short simulation and an analytic approximation. The method exhibits good accuracy and significant improvement in efficiency.< <ETX xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">&gt;</ETX>