Dynamic Channel Allocation Algorithm Research Articles

An Adaptive Dynamic Channel Allocation Algorithm Based on a Temporal–Spatial Correlation Analysis for LEO Satellite Networks

Low Earth orbit (LEO) satellites that can be used as computing nodes are an important part of future communication networks. However, growing user demands, scarce channel resources and unstable satellite–ground links result in the challenge to design an efficient channel allocation algorithm for the LEO satellite network. Edge computing (EC) provides sufficient computing power for LEO satellite networks and makes the application of reinforcement learning possible. In this paper, an adaptive dynamic channel allocation algorithm based on a temporal–spatial correlation analysis for LEO satellite networks is proposed. First, according to the user mobility model, the temporal–spatial correlation of handoff calls is analyzed. Second, the dynamic channel allocation process in the LEO satellite network is formally described as a Markov decision process. Third, according to the temporal–spatial correlation, a policy for different call events is designed and online reinforcement learning is used to solve the channel allocation problem. Finally, the simulation results under different traffic distributions and different traffic intensities show that the proposed algorithm can greatly reduce the rejection probability of the handoff call and then improve the total performance of the LEO satellite network.

Dynamic Channel Allocation Algorithm for Heterogeneous Cellular Networks in Power Communication

In order to solve the problems of low efficiency and high noise in the application of modern channel resource allocation methods, an anti-interference dynamic channel allocation algorithm for heterogeneous cellular networks in power communication is proposed. First, the heterogeneous cellular network model of power communication and the architecture of power multi-channel transmission platform are constructed. Then, according to the receiving and noise characteristics of communication resources, the anti-interference algorithm of power communication resources under multi-channel transmission is designed to obtain the communication index of power communication heterogeneous cellular network, and the anti-interference dynamic allocation algorithm of power communication heterogeneous cellular network resources is realized, Finally, the comparison method is used to prove the practicability of the method in this paper. The experimental results show that the average value of communication resources after interference suppression is 950 Mb, the average signal to noise ratio is 10.5 dB, and the resource allocation time is less than 3 min after 5000 iterations, which is superior to the comparison method. The method has good channel anti-interference ability and channel resource allocation efficiency, and has certain application value.

Energy-efficient dynamic channel allocation algorithm in wireless body area network

Energy-efficient dynamic channel allocation algorithm in wireless body area network

Link Interference and Route Length Based Dynamic Channel Allocation Algorithm for Multichannel Wireless Mesh Networks

In this paper, the theoretical analysis showed that the length of the route and the interference of links were the main factors that influence the throughput of the network. Then, a dynamic channel allocation algorithm base on the length of routes and the interference of links was proposed to enhance the system throughput. In the proposed algorithm, ant colony algorithm was used to collect the information of network, such as the length of routes and the interference of links. Then, the priority of link access channel was decided according to the collected information. The simulation results showed that the proposed algorithm could improve the whole network throughput obviously.

Improvement of the Handover Performance and Channel Allocation Scheme using Fuzzy Logic, Artificial Neural Network and Neuro-Fuzzy System to Reduce Call Drop in Cellular Network

Due to handover failure, call drop occurs frequently. When a large number of incoming and handoff calls arrive at the same time, the performance of the conventional handoff algorithms may fall down. Moreover, multiple factors such as signal quality and available channels of cellular network can’t be evaluated in conventional algorithms. When mobile station (MS) moves, the connection of MS with nearby base station (BS) has to be switched from one to adjacent station. In this case, unnecessary handoffs will be occurred due to lack of proper decision of handoffs or lack of consideration about signal quality with available free channels. As a result call drop will occur frequently. For performing handoff efficiently, fuzzy logic based handoff decision algorithm, adaptive handoff threshold level using neural network and priority based dynamic channel allocation algorithm using neuro-fuzzy system has been proposed in this work. These algorithms will mainly focus on the proper decision of handoff based on evaluating signal strength, available free channels, spectrum efficiency, MS speed and distance from BS so that unnecessary and inefficient handoffs can’t be performed. Simulation revealed that using neuro-fuzzy system, the channel capacity, SIR and Handoff management were improved better than the others in terms of spectrum utilization efficiency, MS speed and SIR. The efficacy of the methodology has been proved by imitating the proposed model using MATLAB software.

Human-Behavior and QoE-Aware Dynamic Channel Allocation for 5G Networks: A Latent Contextual Bandit Learning Approach

With the rapid advance of smart wireless technologies, a plethora of human behavioral data are generated in 5G networks, which is reported capable to improve network performance by leveraging intelligent channel resource allocation through big data analytics. However, what information can be extracted for the network mobility management, how to exploit the knowledge for resource allocation and to meet the user-centric quality of experience (QoE) are not well understood and fully explored. To address this problem, we propose an online learning algorithm for dynamic channel allocation based on contextual multi-armed bandit (CMAB) theory. Especially, we divide the stochastic human behavioral data into two categories: the user location and the QoE-driven context. Noticing that the distributions of CSI vary spatially, we define a set of user’s geographic locations that shares the same set of CSI distributions as a cluster , and the stochastic channel distributions vary across clusters. The problem is formulated as a novel latent SCB problem, where the proposed agnostic SCB algorithm could automatically find the underlying clusters and significantly improve the learning performance. We then extend our online learning algorithm into the practical multi-user random access scenario. We conduct experiments on a real dataset collected from China Mobile, which indicate that our algorithms outperform existing approaches tremendously and perform extremely well in large-scale and high-mobility networks.

Deep Reinforcement Learning Based Dynamic Channel Allocation Algorithm in Multibeam Satellite Systems

Dynamic channel allocation (DCA) is the key technology to efficiently utilize the spectrum resources and decrease the co-channel interference for multibeam satellite systems. Most works allocate the channel on the basis of the beam traffic load or the user terminal distribution of the current moment. These greedy-like algorithms neglect the intrinsic temporal correlation among the sequential channel allocation decisions, resulting in the spectrum resources underutilization. To solve this problem, a novel deep reinforcement learning (DRL)-based DCA (DRL-DCA) algorithm is proposed. Specifically, the DCA optimization problem, which aims at minimizing the service blocking probability, is formulated in the multibeam satellite systems. Due to the temporal correlation property, the DCA optimization problem is modeled as the Markov decision process (MDP) which is the dominant analytical approach in DRL. In modeled MDP, the system state is reformulated into an image-like fashion, and then, convolutional neural network is used to extract useful features. Simulation results show that the DRL-DCA algorithm can decrease the blocking probability and improve the carried traffic and spectrum efficiency compared with other channel allocation algorithms.

Distributed Learning for Energy-Efficient Resource Management in Self-Organizing Heterogeneous Networks

In heterogeneous networks, a dense deployment of base stations (BSs) leads to increased total energy consumption, and, consequently, increased cochannel interference (CCI). In this paper, to deal with this problem, self-organizing mechanisms are proposed, for joint channel and power allocation procedures, which are performed in a fully distributed manner. A dynamic channel allocation mechanism is proposed, in which the problem is modeled as a noncooperative game, and a no-regret learning algorithm is applied for solving the game. In order to improve the accuracy and reduce the effect of shadowing, we propose another channel allocation algorithm executed at each user equipment (UE). In this algorithm, each UE reports the channel with minimum CCI to its associated BS. Then, the BS selects its channel based on these received reports. To combat the energy consumption problem, BSs choose their transmission power by employing an on – off switching scheme. Simulation results show that the proposed mechanism, which is based on the second proposed channel allocation algorithm and combined with the on–off switching scheme, balances load among BSs. Furthermore, it yields significant performance gains up to about $40.3\%$ , $44.8\%$ , and $70.6\%$ in terms of average energy consumption, UE's rate, and BS's load, respectively, compared to a benchmark based on an interference-aware dynamic channel allocation algorithm.

A Dynamic Channel Allocation Algorithm in TD-SCDMA System

In the TD-SCDMA system, there is a problem that non-emergency voice services probability of dropped call is not ideal when we use the dynamic allocation algorithm. To solve this problem, we propose a new algorithm, which is called protect channel reservation queue movable boundary dynamic channel allocation. This algorithm set aside channels for dropped calls of non-emergency voice services service, in order to keep blocking probability for service, the introduction of no patient customers, combined with the data packet to borrow algorithms. Simulation results show that, comparing to the movable boundary algorithm, the proposed algorithm reduce the drop probability for non-emergency voice services, and maintain a variety of service blocking probability, reducing the packet loss probability data services.

An Improved DCA and Channel Modelling Algorithm Based on Carrier Priority in LTE/LTE-A

Dynamic Channel Allocation (DCA) technology is an effective ways to solve the contradiction between limited spectrum resources and increasing user demand in TD-SCDMA system. Aiming at the limitation of conventional DCA algorithm, an improved dynamic channel allocation algorithm based on carrier priority is proposed in this paper to solve tidal phenomenon caused by regional traffic migration and shows channel model. The simulation results show that the proposed algorithm can effectively increase resource utilization and improve access success rate with less changing in channel model.

DynaChannAl: dynamic channel allocation with minimal end‐to‐end delay for two‐tier wireless sensor networks

ABSTRACTWith recent advances in wireless networking and in low‐power sensor technology, wireless sensor networks (WSNs) have taken significant roles in various applications. Whereas some WSNs only require minimal bandwidth, newer applications operate with a noticeably larger amount of data. One way to deal with these applications is to maximize the available capacity by utilizing multiple wireless channels. We propose DynaChannAl, a distributed dynamic wireless channel allocation algorithm that effectively distributes nodes to multiple wireless channels in WSNs. Specifically, DynaChannAl targets applications where mobile nodes connect to preexisting wireless backbones and takes the expected end‐to‐end queuing delay as its core metric. We used the link quality indicator values provided by 802.15.4 radios to whitelist high‐quality links and evaluate these links with the aggregated queuing latency, making it useful for applications that require minimal end‐to‐end delay (i.e., health care). DynaChannAl is a lightweight and adoptable scheme that can be incorporated easily with predeveloped systems. As the first study to consider end‐to‐end latency as the core metric for channel allocation in WSNs, we evaluate DynaChannAl on a 45 node test bed and show that DynaChannAl successfully distributes source nodes to different channels and enables them to select channels and links that minimizes the end‐to‐end latency. Copyright © 2012 John Wiley & Sons, Ltd.

CHANNEL SHARING SCHEME FOR CELLULAR NETWORKS USING MDDCA PROTOCOL IN WLAN

In cellular networks, it is vital to allocate communication channels efficiently because the bandwidth allocated for cellular communication is limited. When mobile hosts move from one cell to another cell, to provide uninterrupted service, the new cell should have enough channels to support the ongoing communication of the mobile hosts that moved into the cell. If channels are statically allocated, a cell may run out of channels when large number of mobile hosts moves to a cell, thus degrading the quality of service. To overcome this problem, dynamic channel allocation approaches have been proposed which allocate channels to cells on demand, thus increasing channel utilization and hence improving the quality of service. A distributed dynamic channel allocation algorithms gained a lot of attention due to their high reliability and scalability. The cell that wants to borrow a channel has to wait for replies from all its interference neighbors and hence, is not fault-tolerant. This work aims to propose a Distributed dynamic channel allocation algorithm to make use of the available channel efficiently. It can tolerate the failure of mobile nodes as well as static nodes and enhance the quality of service by making efficient reuse of channels. This paper proposes a channel allocation scheme with efficient bandwidth reservation, which initially reserves some channels for handoff calls, and later reserves the channels dynamically, based on the user mobility The results indicate that the proposed channel allocation scheme exhibits better performance by considering the above mentioned user mobility, type of cells, and maintaining of the queues for various traffic sources. In addition, it can be observed that our approach reduces the dropping probability by using reservation factor.

Interference-Adaptive Fast Dynamic Channel Allocation in TD-SCDMA System

This paper proposes a new priority metric for fast dynamic channel allocation (DCA) in TD-SCDMA system, which reallocates radio resource units (RUs) to bearer services in a cell. It allows for developing a new interference-adaptive fast DCA algorithm, which is more flexible with a non-uniform user distribution. It considers the relative transmission opportunities with respect to the residual capacity and co-channel interference levels for all users, which steadily varies in the real communication environment. The proposed fast DCA algorithm aims to fully utilize the physical resource available in the time-division duplexing (TDD)-based CDMA system subject to the various types of inter-cell interference, as opposed to most existing algorithms in which traffic load and quality of service cannot be jointly balanced among the multiple radio resource units in a flexible manner. The simulation results show that the proposed algorithm improves the outage performance while reducing the average system interference, achieving full utilization of the physical resource, i.e., 48 RUs in TD-SCDMA, over a wide range of acceptable outage performance.

Fairness-insured Aggressive Sub-channel Allocation and Efficient Power Allocation Algorithms to Optimize the Capacity of an IEEE 802.16e OFDMA/TDD Cellular System

This paper aims to find a suitable solution to joint allocation of sub-channel and transmit power for multiple users in an IEEE 802.16e OFDMA/TDD cellular system. We propose the FASA (Fairness insured Aggressive Sub-channel Allocation) algorithm, which is a dynamic channel allocation algorithm that considers all of the users' channel state information conditionally in order to maximize throughput while taking into account fairness. A dynamic power allocation algorithm, i.e., an improved CHC algorithm, is also proposed in combination with the FASA algorithm. It collects the extra downlink transmit power and re-allocates it to other potential users. Simulation results show that the joint allocation scheme with the improved CHC power allocation algorithm provides an additional increase of sector throughput while simultaneously enhancing fairness. Four frames of time delay for CQI feedback and scheduling are considered. Furthermore, by addressing the difference between uplink and downlink scheduling in an IEEE 802.16e OFDMA TDD system, we can employ the uplink channel information directly via channel sounding, resulting in more accurate uplink dynamic resource allocation.

Fast system load estimation in the IEEE 802.16 OFDMA network

Considering the network system load in the call admission control, adaptive transmission, handover, and dynamic channel allocation algorithms is a promising approach in the IEEE 802.16 orthogonal frequency division multiple access (OFDMA) network. In this paper we estimate the system load of the IEEE 802.16 OFDMA network. Our system load model comprises the uplink load, the downlink load, the sector load, and the network load. To estimate the uplink, downlink, and sector loads the conditional optimization problems should be solved. The optimal solution to these problems is the exhaustive search, which, however is inapplicable in practice. In this paper we propose fast algorithms that solve these optimization problems.

Supporting Asymmetric Traffic in a TDD/CDMA Cellular Network via Interference-Aware Dynamic Channel Allocation and Space–Time LMMSE Joint Detection

In a time-division duplexing (TDD)/code-division multiple-access (CDMA) cellular network with asymmetric data traffic, dynamic channel allocation (DCA) enhances resource utilization compared with fixed channel allocation (FCA). However, it also induces base-to-base and mobile-to-mobile crossed-slot intercell interference, which can severely degrade system performance. To deal with this problem, a decentralized scheme is proposed, which combines an interference-aware DCA algorithm with space-time linear minimum-mean-square-error (LMMSE) joint detection at the base and mobile stations. The former assigns active links to timeslots in a way that crossed-slot interference is mitigated, while the latter suppresses the remaining intercell interference (along with intersymbol and intracell interference), exploiting its spatio-temporal autocorrelation statistics. The performance of this scheme is evaluated in terms of downlink and uplink signal-to-interference-plus-noise ratio (SINR) outage and average throughput via analytical approximations and Monte Carlo simulations, and it is compared with that of benchmark random DCA (RDCA) and FCA schemes. The cases of single- and dual-antenna reception with perfect and imperfect channel state information are examined. It is shown that the proposed scheme achieves higher average throughput than FCA (particularly for dual-antenna reception) as well as RDCA (for heavy traffic loads). These throughput gains are more significant in uplink than in downlink.

Location-based QoS enhanced dynamic carrier allocation over multi-cell environments

It is well known that high multi-user and multi-carrier diversity gains can be achieved via the use of DCA (Dynamic Channel Allocation). However, there is no framework for analyzing the system performance of DCA algorithms over multi-cell environments. This paper presents a numerical analysis for measuring the performance gain for various DCA algorithms. Based on the analysis, an LQE (Location-based QoS Enhanced) DCA algorithm is proposed, in which a higher priority is assigned to users in the outer region for fairness by exploiting multi-carrier diversity. In the inner region, each carrier is allocated to a user with the best channel gain for higher throughput by exploiting multi-user diversity. In the simulation, we demonstrate that the proposed DCA algorithm is very effective from the perspective of fairness and throughput.

Channel allocation and medium access control for wireless sensor networks

Recent developments in sensor technology, as seen in Berkeley’s Mica2 Mote, Rockwell’s WINS nodes and the IEEE 802.15.4 Zigbee, have enabled support for single-transceiver, multi-channel communication. The task of channel assignment with minimum interference, also named as the 2-hop coloring problem, allows repetition of colors occurs only if the nodes are separated by more than 2 hops. Being NP complete, development of efficient heuristics for this coloring problem is an open research area and this paper proposes the Dynamic Channel Allocation (DCA) algorithm as a novel solution. Once channels are assigned, a Medium Access Control protocol must be devised so that channel selection, arbitration and scheduling occur with maximum energy savings and reduced message overhead, both critical considerations for sensor networks. The contribution of this paper is twofold: (1) development and analysis of the DCA algorithm that assigns optimally minimum channels in a distributed manner in order to make subsequent communication free from both primary and secondary interference and (2) proposing CMAC, a fully desynchronized multi-channel MAC protocol with minimum hardware requirements. CMAC takes into account the fundamental energy constraint in sensor nodes by placing them in a default sleep mode as far as possible, enables spatial channel re-use and ensures nearly collision free communication. Simulation results reveal that the DCA consumes significantly less energy while giving a legal distributed coloring. CMAC, our MAC protocol that leverages this coloring, has been thoroughly evaluated with various modes in SMAC, a recent protocol that achieves energy savings through coordinated sleeping. Results show that CMAC obtains nearly 200% reduction in energy consumption, significantly improved throughput, and end-to-end delay values that are 50–150% better than SMAC for our simulated topologies.

A Cost-Function-Based Dynamic Channel Allocation and Its Limits

Design of efficient dynamic channel allocation (DCA) algorithms has an important impact on performance optimization of wireless mobile networks. The previously proposed DCA algorithms are shown to have good performance but only for certain services and under certain load conditions. Within this paper, we propose a new cost-function-based DCA algorithm, which is fully adaptive to service and load conditions and includes some well-known DCA algorithms such as random, minimum interference, and autonomous reuse partitioning DCA as special cases. By using dynamic system-level simulations, we show that the algorithm provides the same or substantially better performance than these DCA algorithms, with low signalization and computation overhead. We also show the general limits of DCA algorithms in the presence of other interference reduction techniques such as power control and smart antennas.

Blocking Probability of a DS-CDMA Multi-Hop Virtual Cellular Network

A wireless multi-hop virtual cellular network (VCN) was recently proposed to avoid the large peak transmit power, resulting from the high transmission rates expected for future mobile communication systems. In VCN, calls hop through several links to reach the central port, which is the gateway to the network. With the use of a routing algorithm based on the total uplink transmit power minimization criterion, the total transmit power of all the multi-hop links between the mobile terminal and the central port can be significantly reduced, in comparison with the present (single-hop) cellular network. In this paper, an on-demand channel assignment strategy, using the channel segregation dynamic channel allocation (CS-DCA) algorithm, is proposed for multi-hop DS-CDMA VCN. Computer simulation is conducted to evaluate the blocking probability performance and make a comparison between the VCN and the present cellular network.