Channel Allocation Methods Research Articles

Frequency allocation algorithm

Wireless communication technology's quick advancement has facilitated the ongoing formation of numerous new communication business scenarios and the thorough connectivity of man-machine-object-space. The conflict between few channel resources and high demand is becoming more and more obvious, which adds to the stress on the entire network. In order to enhance communication quality with constrained frequency resources, more optimal channel allocation techniques are urgently required. This paper discusses the increasing demand for frequency resources due to the exponential growth of data traffic, which has necessitated more efficient channel allocation methods to optimize communication quality with limited frequency resources. The evolution of mobile wireless cellular communication systems from the first generation to the current fifth generation, and the imminent emergence of the sixth generation, are also discussed. The paper highlights the importance of ultra-dense networks and device-to-device communication in meeting the capacity and coverage requirements of 5G networks. The advantages and disadvantages of different frequency reuse methods, specifically Fractional Frequency Reuse (FFR) and water injection algorithm, are analyzed. The paper summarizes these methods' principles and application effects in specific situations, emphasizing the need for appropriate frequency reuse methods to achieve optimal channel allocation and communication quality.

Comparison of Different Frequency Channel Allocation Methods in ultra-dense networks

The impact of information transmission on production and life under dense networking is self-evident. Dense networking application scenarios include airports, dense residential buildings, dense business districts and blocks, campuses, large gatherings, stadiums, subways, etc. However, with the increase of 5G frequency band, the 5G macro base station signal attenuates more when it penetrates the wall than 4G, which makes it difficult to cover indoor signals. The outdoor 5G macro base station signal can only provide shallow indoor coverage after penetrating obstacles such as brick walls, glass and cement, which cannot guarantee the good experience required for indoor deep coverage. This paper compares and discusses various channel allocation algorithms based on user scenarios in ultra-dense networks. By adjusting some parameters of 19 units, the integer frequency reuse (IFR) method (N=1,3), fractional frequency reuse (FFR) method, simultaneous water injection (SWF) method, and transmission interference temperature limit (TX-ITL) method are compared. In order to increase the capacity, a combination of several algorithms will also be used.

Multi-Armed-Bandit Based Channel Selection Algorithm for Massive Heterogeneous Internet of Things Networks

In recent times, the number of Internet of Things devices has increased considerably. Numerous Internet of Things devices generate enormous traffic, thereby causing network congestion and packet loss. To address network congestion in massive Internet of Things systems, an efficient channel allocation method is necessary. Although some channel allocation methods have already been studied, as far as we know, there is no research focusing on the implementation phase of Internet of Things devices while considering massive heterogeneous Internet of Things systems where different kinds of Internet of Things devices coexist in the same Internet of Things system. This paper focuses on the multi-armed-bandit-based channel allocation method that can be implemented on resource-constrained Internet of Things devices with low computational processing ability while avoiding congestion in massive Internet of Things systems. This paper first evaluates some well-known multi-armed-bandit-based channel allocation methods in massive Internet of Things systems. The simulation results show that an improved multi-armed-bandit-based channel selection method called Modified Tug of War can achieve the highest frame success rate in most cases. Specifically, the frame success rate can reach 95% when the numbers of channels and IoT devices are 60 and 10,000, respectively, while 12% channels are suffering traffic load by other kinds of IoT devices. In addition, the performance in terms of frame success rate can be improved by 20% compared to the equality channel allocation. Moreover, the multi-armed-bandit-based channel allocation methods is implemented on 50 Wi-SUN Internet of Things devices that support IEEE 802.15.4g/4e communication and evaluate the performance in frame success rate in an actual wood house coexisting with LoRa devices. The experimental results show that the modified multi-armed-bandit method can achieve the highest frame success rate compared to other well-known frame success rate-based channel selection methods.

Modified PSO Based Channel Allocation Scheme for Interference Management in 5G Wireless Mesh Networks

Efficient channel management is a challenge that next-generation wireless networks need to meet in order to satisfy increasing bandwidth demand and transmission rate requirements. Non-orthogonal multiple access (NOMA) is one of such efficient channel allocation methods used in 5G backhaul wireless mesh networks. In this paper, we propose a power demand-based channel allocation method for 5G backhaul wireless mesh networks by employing NOMA and considering traffic demands in small cells, thereby improving channel utility. In this scheme, we work with physical layer transmission. The foremost aim is to mutually optimize the uplink/downlink NOMA channel assignment in order to increase user fairness. The approach concerned may be divided into two steps. First, initial channel allocation is performed by employing the traveling salesman problem (TSP), due to its similarity to many-to-many double-side user-channel allocation. Second, the modified particle swarm optimization (PSO) method is applied for allocation updates, by introducing a decreasing coefficient which may have the form of a standard stochastic estimate algorithm. To enhance exploration capacity of modified the PSO, a random velocity is included to optimize the convergence rate and exploration behavior. The performance of the designed scheme is estimated through simulation, taking into account such parameters as through put, spectral efficiency, sum-rate, outage probability, signal to-interference plus noise ratio (SINR), and fairness. The proposed scheme maximizes network capacity and improves fairness between the individual stations. Experimental results show that the proposed technique performs better than existing solutions.

Intelligent Channel Allocation for Age of Information Optimization in Internet of Medical Things

Along with the development of realtime applications, the freshness of information becomes significant because the overdue information is worthless and useless and even harmful to the right judgement of system. Therefore, The Age of Information (AoI) used for marking the freshness of information is proposed. In Internet of Medical Things (IoMT), which is derived from the requirement of Internet of Thins (IoT) in medicine, high freshness of medical information should be guaranteed. In this paper, we introduce the AoI of medical information when allocating channels for users in IoMT. Due to the advantages of Deep Q‐learning Network (DQN) applied in resource management in wireless network, we propose a novel DQN‐based Channel Allocation (DQCA) algorithm to provide the strategy for channel allocation under the optimization of the system cost considering the AoI and energy consumption of coordinator nodes. Unlike the traditional centralized channel allocation methods, the DQCA algorithm is distributed as each user performs the DQN process separately. The simulation results show that our proposed DQCA algorithm is superior to Greedy algorithm and Q‐learning algorithm in terms of the average AoI, average energy consumption and system cost.

Location-partition-based channel allocation and power control methods for C-V2X communication networks

This paper studies the resource allocation (RA) problem in a vehicle-to-vehicle (V2V) communication network when the in-band device-to-device technology is applied to support cellular-based vehicle-to-everything communication. Due to the rapid mobility of vehicles, it is difficult to track real-time channel state information so that effective RA is challenging. We consider a scenario where multiple V2V links on a road can be divided into groups to reuse cellular users’ channels. A location-partition-based channel allocation (CA) scheme is first proposed by transforming the CA problem into a simple data-matching problem. Further, a best-effort rate-equal power control scheme is studied to maximize the minimum achievable rate among the V2V links in one group. Two other schemes are proposed to improve the communication latency in high-density environments. Simulation results show that the performance of the proposed RA approaches is better than conventional solutions.

Sustainable Communication Systems: A Graph-Labeling Approach for Cellular Frequency Allocation in Densely-Populated Areas

The need for smart and sustainable communication systems has led to the development of mobile communication networks. In turn, the vast functionalities of the global system of mobile communication (GSM) have resulted in a growing number of subscribers. As the number of users increases, the need for efficient and effective planning of the “limited” frequency spectrum of the GSM is inevitable, particularly in densely-populated areas. As such, there are ongoing discussions about frequency (channel) allocation methods to resolve the challenges of channel allocation, which is a complete NP (Nondeterministic Polynomial time) problem. In this paper, we propose an algorithm for channel allocation which takes into account soft constraints (co-channel interference and adjacent channel interference). By using the Manhattan distance concept, this study shows that the formulation of the algorithm is correct and in line with results in the literature. Hence, the Manhattan distance concept may be useful in other scheduling and optimization problems. Furthermore, this unique concept makes it possible to develop a more sustainable telecommunication system with ease of connectivity among users, even when several subscribers are on a common frequency.

Enlarge Storing Concept in an Efficient Handoff Allocation during Travel by Time Based Algorithm

Objectives: During travelling mobile hosts move from one cell to another cell, to deliver continuous service, the new cell would have sufficient 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. Because allocation of cells statically without knowing the proper information hold most cells so it will decrease the quality of service of cellular network. Methods/Statistical Analysis: To overwhelm this problem, dynamic channel allocation methods have been proposed which allocate channels to cells on request, thus cumulative channel consumption and hence improving the quality of service. This scheme aimed at minimizing the effect of assigned channels on the availability of them in order to use in the interfering cells and reduce their overall reuse distance. Findings: The system shows better performance when the channels are distributed uniformly/non-uniformly with queues using the frequency reuse scheme. In order to support QoS in cellular networks it is a significant issue to allocate the communication channels efficiently because the bandwidth allocated for the cellular communication. The existing system used channel allocation system, based on traffic and priority, but it is not enough. Applications/Improvements: The proposed system is designed based on the time of entering of the cellular node in a new allocated cell and the time period for the particular cell stayed in the previous cell. So it is better for the travelling cellular networks. This research work focus only on a class of applications needing hard QoS guarantee. A more interesting work will address how to allocate.

Survey on Channel Allocation Techniques for Wireless Mesh Network to Reduce Contention with Energy Requirement

Objective: In Wireless Mesh Networks the spectrum should be utilized effectively with better Quality of Service (QoS), synchronized time management and minimum delay. Method: The existing channel allocation methods needs improvement in QoS parameters such as end-to-end delay, ripple factor and time factor in accessing the channel. To improve the QoS further, the admission control drop and block probability, efficient channel reservation approach is the better solution which leads to better QoS even for delay sensitive applications. A performance analysis is made among the existing methods for contention reduced channel allocation methods, energy conservation channel allocation methods and as last method Admission Control Drop_Block probability methods. The networks are analyzed by considering the metrics such as Packet loss rate, End-to-end delay and Throughput. The channel count is virtually increased to support for dense networks by utilizing already used channels and by reserving few channels for dynamic requirement for normal and multimedia traffic data. The channel allocation methods are simulated using NS-2.

Channel allocation for hot spot areas in HAPS communication based on the prediction of mobile user characteristics

AbstractHigh altitude platform station (HAPS) communication employs multiple high altitude platforms with the same bandwidth in order to serve the same region. This working mode greatly increases user capacity and improves frequency spectrum utilization, thus endowing HAPS communication with its superiority in solving hot spot issues. In this study, a standard for deciding the minimum distance in mobile user access systems was derived. Using this standard, channel allocation approaches based on the prediction of user number change and call volume change were proposed. These proposed approaches could effectively remove the problem of insufficient or wasted channels caused by the lack of proactive cooperation in conventional channel allocation methods. These approaches are validated through simulation, in which the proposed channel allocation approaches demonstrated the reasonable allocation of channels and the avoidance of call blocking while improving the utilization of channels.

Fair and QoS-oriented resource management in heterogeneous networks

In this paper, a heterogeneous network composed of femtocells deployed within a macrocell network is considered, and a quality-of-service (QoS)-oriented fairness metric which captures important characteristics of tiered network architectures is proposed. Using homogeneous Poisson processes, the sum capacities in such networks are expressed in closed form for co-channel, dedicated channel, and hybrid resource allocation methods. Then a resource splitting strategy that simultaneously considers capacity maximization, fairness constraints, and QoS constraints is proposed. Detailed computer simulations utilizing 3GPP simulation assumptions show that a hybrid allocation strategy with a well-designed resource split ratio enjoys the best cell-edge user performance, with minimal degradation in the sum throughput of macrocell users when compared with that of co-channel operation.

Localized or Interleaved? A Tradeoff between Diversity and CFO Interference in Multipath Channels

Carrier frequency offset (CFO) damages the orthogonality between sub-carriers and thus causes multiuser interference in uplink OFDMA/SC-FDMA systems. For a given CFO, such multiuser interference is mainly dictated by channel (sub-carrier) allocation, which also specifies the diversity gain of one user over multi-path channels. In particular, the positions of one user's sub-channels will determine its diversity gain, while the distances between sub-channels of the concerned user and those of others will govern the CFO interference. Two popular channel allocation methods are the localized and interleaved (distributed) schemes where the former has less CFO interference but the latter achieves more diversity gain. In this paper, we will consider the channel allocation scheme for uplink LTE systems by investigating the effects of channel allocation on both of the diversity gain and CFO interference. By combining these two effects, we will propose a semi-interleaved scheme, which achieves full diversity gain with minimum CFO interference.

Reducing latency through efficient channel allocation methods for multiversion data dissemination in mobile computing environment

This paper focuses on channel allocation methods for multiversion data dissemination in mobile computing systems in which maximizing data currency (minimizing staleness) and minimizing the mean response time are of equal importance as providing consistent data items to mobile transactions. We propose broadcast marshalling method that clusters data to be broadcast, depending on their access frequencies, to reduce mean response time of the mobile clients. We consider two basic multiversion data organizations, namely vertical and horizontal data organizations and it uses an efficient mobile data compression technique, with minimal impact on the client, to efficiently use the low bandwidth of mobile communication systems and to reduce the mean access delay for data items and minimize the response times of the requests from the mobile clients. The broadcast and on-demand channels have different access performance under different system parameters and that a mobile cell should use a combination of both to obtain optimal access time for a given workload and system parameters. We study the data access efficiency of three channel configurations: i) all channels are used as on-demand channels (exclusive on-demand), ii) all channels are used for broadcast (exclusive broadcast) and iii) some channels are on-demand channels and some are broadcast channels (hybrid). Simulations on obtaining the optimal channel allocation, with two different Multiversion data organizations combined with compression scheme, were conducted and the result shows that the method significantly improves the system performance.

Design issues of uplink media access control (MAC) protocols for multimedia traffic over DS-CDMA systems

We propose an efficient uplink media access control (MAC) protocol for a variable spreading gain interference-limited wideband CDMA system. It can, with high spectral efficiency, support both real-time traffic like speech and video and also nonreal-time data traffic based on packet transmission. The schemes for power allocation, joint scheduling, and transmission rate adaptation for nonreal time data traffic are designed as integrated parts of the MAC, working together to improve the system performance in terms of capacity and delay. With these associated resource management mechanisms, the performances of the MAC protocol with two different channel-allocation methods for real-time traffic are numerically compared. One is demanding channel allocation, and the other is reserve channel allocation, in which a certain bandwidth is reserved for concurrent real-time traffic.

Bandwidth-Efficient WDM Channel Allocation for Four-Wave Mixing-Effect Minimization

A novel channel-allocation method that allows reduction of the four-wave mixing (FWM) effect while maintaining bandwidth efficiency is presented. It is composed of a fractional bandwidth-allocation algorithm, taking into consideration the use of parameters with distinct differences. This proposed technique allows the computation of an optimal channel-allocation set, where degradation caused by interchannel interference and FWM is minimal. Simulation is carried out to show significant performance improvement, such as an average bit-error rate improvement factor of 1.336 for an eight-channel wavelength-division multiplexing system, without the requirement of increased bandwidth, unlike existing channel-allocation methods.

Channel allocation algorithm for WDM systems

An algorithm for WDM channel allocation, based on the concept of Optimal Golomb Ruler (OGR), is proposed. This algorithm enhances system performance by locating an allocation set, where the degradation caused by the effects of interchannel interference and Four-Wave Mixing (FWM) is minimal. Two sets of simulation were performed on an 8x10Gbpschannel system (channel spacing of 50GHz for equally spaced allocation), with 50% pre-allocated bandwidth using non-zero dispersion-shifted fibers with dispersion of 3 and 6ps/nm.km at 1550nm. Results showed BER improvement of 1.75 and 0.97 for the 3 and 6ps/nm.km simulations respectively. This improvement is significant, considering the fact that no additional cost (bandwidth) was incurred, unlike existing unequally spaced channel allocation methods.

A study on channel allocation for data dissemination in mobile computing environments

This paper studies channel allocation methods for data dissemination through broadcast and on-demand channels. Analytical models and cost formulae for exclusive broadcast channels and exclusive on-demand channels are provided. Based on the models, we further derive cost models for dynamic channel allocation methods and propose a channel adaptation algorithm for optimizing system performance. The channel adaptation algorithm can be executed in O(n) time, where n is the number of data items in the database. Performance evaluation shows that the channel allocation algorithm produces optimal channel allocation which significantly improves the system performance under various parameter settings.

Dynamic channel allocation in interference-limited cellular systems with uneven traffic distribution

Most recently proposed wireless dynamic channel allocation methods have used carrier-to-interference (C/I) information to increase the system performance. Power control is viewed as essential for interference-limited systems. However, the performance of such systems under an imbalance of load among cells, as may occur often in microcells, is largely unknown. Here, we study a typical interference-limited dynamic channel allocation policy. Calls are accepted if a channel can be assigned that will provide a minimum C/I, and power control and intracell handoffs are used to maintain this level. We focus on the relationship between system performance and the amount of imbalance in load among neighboring cells. Previous studies for systems that do not use C/I information have found that dynamic channel allocation (DCA) outperforms fixed channel allocation (FCA) in all but heavily loaded systems with little load imbalance. We present two principal new results. First, we find that with use of C/I information, the difference in performance between FCA and DCA (in terms of throughput or blocking probability) is increasing with load imbalance. DCA was found to be more effective in congestion control at the cost of a slightly lower call quality. Second, we find that use of power control to maintain a minimum C/I results in two equilibrium average power levels for both DCA and FCA, with DCA using a higher average power than FCA, and that while DCA's power is increasing with load imbalance, FCA's average power is decreasing with load imbalance.

Exact SINR Calculations for Optimum Linear Combining in Wireless Systems

This paper presents an exact derivation of the statistical distribution of the signal to interference-plus-noise ratio (SINR) for optimum linear combining in wireless systems with multiple cochannel interferes, Rayleigh fading, and additive white Gaussian noise. The distribution of the SINR is shown to be remarkably simple and leads to bounds on the bit error rate and outage probabilities which are tighter, simpler, and more robust than any previous results. The simplicity of the SINR distribution permits extremely fast computation of outage probabilities for any number of interference channels and diversity levels. Hence for wireless systems it enables performance studies to be performed over a much wider range of conditions, such as shadow fading, specific channel allocation methods, etc. Previously such studies were extremely limited due to the intensive computational requirements of simulating these systems.

Modelling of dynamic flows in cellular mobile networks

Abstract A mathematical model that predicts the dynamic flows in cellular mobile networks with handoff procedures is described in this paper. Two types of handoff procedures considered in the model are the non-prioritized and the prioritized or reserved channel schemes. The dynamic behaviour of this model makes it suitable to analyse dynamic channel allocation methods as well as to analyse the robustness of the system under perturbation. The basic concept of our model is based on the fluid flow theory and the queueing theory. Discrete event simulations were performed and the results were found to be comparable to the results obtained using the mathematical model.