scholarly journals Intelligent Resource Allocation Method for Wireless Communication Networks Based on Deep Learning Techniques

2021 ◽  
Vol 2021 ◽  
pp. 1-12
Author(s):  
Hancheng Hui

In this paper, a deep learning approach is used to conduct an in-depth study and analysis of intelligent resource allocation in wireless communication networks. Firstly, the concepts related to CSCN architecture are discussed and the throughput of small base stations (SBS) in CSCN architecture is analyzed; then, the long short-term memory network (LSTM) model is used to predict the mobile location of users, and the transmission conditions of users are scored based on two conditions, namely, the mobile location of users and whether the small base stations to which users are connected have their desired cache states, and the small base stations select the transmission. The small base station selects several users with optimal transmission conditions based on the scores; then, the concept of game theory is introduced to model the problem of maximizing network throughput as a multi-intelligent noncooperative game problem; finally, a deep augmented learning-based wireless resource allocation algorithm is proposed to enable the small base station to learn autonomously and select channel resources based on the network environment to maximize the network throughput. Simulation results show that the algorithm proposed in this paper leads to a significant improvement in network throughput compared to the traditional random-access algorithm and the algorithm proposed in the literature. In this paper, we apply it to the fine-grained resource control problem of user traffic allocation and find that the resource control technique based on the AC framework can obtain a performance very close to the local optimal solution of a matching-based proportional fair user dual connection algorithm with polynomial-level computational complexity. The resource allocation and task unloading decision policy optimization is implemented, and at the end of the training process, each intelligent body independently performs resource allocation and task unloading according to the current system state and policy. Finally, the simulation results show that the algorithm can effectively improve the quality of user experience and reduce latency and energy consumption.

2021 ◽  
Vol 26 (1) ◽  
pp. 79-85
Author(s):  
Samar Shaker Metwaly ◽  
Ahmed. M. Abd El-Haleem ◽  
Osama El-Ghandour

NB-IoT is the standardized technology for machine type communication (MTC) in Long Term Evolution (LTE). NB-IoT can achieve IoT requirements nevertheless, it suffers a low rate and capacity. On the other hand, Unmanned aerial vehicles (UAV) and Non-Orthogonal Multiple Access (NOMA) are promising technology used to enhance the throughput, capacity, and coverage of wireless communication networks. In this paper, we propose a heterogeneous network scenario where a UAV small Base Station (UBS) is used to assist the LTE Macro Base Station (MBS) with the help of the Non-Orthogonal Multiple Access technique to solve the NB-IoT throughput and capacity issues. Matching game based no-regret learning algorithm is proposed to optimize the NB-IoT device association and using NOMA pairing at each base station to provide the maximum system total rate and capacity. Simulation results show that our proposed scheme increases the total rate of the system by 60% and the system capacity by at least 80%, compared to NOMA without UAV and the total rate and capacity of the system by 200% and 85% respectively, with OMA scheme.


2010 ◽  
Vol 2010 ◽  
pp. 1-7 ◽  
Author(s):  
Lingjia Liu ◽  
Jianzhong (Charlie) Zhang ◽  
Jae-Chon Yu ◽  
Juho Lee

We consider the applications of multicell transmission schemes to the downlink of future wireless communication networks. A multicell multiple-input multiple output-(MIMOs) based scheme with limited coordination among neighboring base stations (BSs) is proposed to effectively combat the intercell interference by taking advantage of the degreesoffreedom in the spatial domain. In this scheme, mobile users are required to feedback channel-related information to both serving base station and interfering base station. Furthermore, a chordal distance-based compression scheme is introduced to reduce the feedback overhead. The performance of the proposed scheme is investigated through theoretical analysis as well as system level simulations. Both results suggest that the so-called “intercell interference coordination through limited feedback” scheme is a very good candidate for improving the cell-edge user throughput as well as the average cell throughput of the future wireless communication networks.


Sensors ◽  
2021 ◽  
Vol 21 (12) ◽  
pp. 4022
Author(s):  
Seong Jung Kim ◽  
Jeong Gon Kim

With the rapid deployment of present-day mobile communication systems, user traffic requirements have increased tremendously. An ultra-dense network is a configuration in which the density of small base stations is greater than or equal to that of the user equipment. Ultra-dense networks are considered as the key technology for 5th generation networks as they can improve the link quality and increase the system capacity. However, in an ultra-dense network, small base stations are densely positioned, so one user equipment may receive signals from two or more small base stations. This may cause a severe inter-cell interference problem. In this study, we considered a coordinated multi-point scenario, a cooperative technology between base stations to alleviate the interference. In addition, to suppress the occurrence of severe interference at the cell edges, link formation was carried out by considering the degree of cell load for each cluster. After the formation of links between all the base stations and user equipment, a subcarrier allocation procedure was performed. The subcarrier allocation method used in this study was based on the location of base stations with clustering to improve the data rate and reduce the interference between the clusters. Power allocation was based on the channel gain between the base station and user equipment. Simulation results showed that the proposed scheme delivered a higher sum rate than the other resource allocation methods reported previously for various types of user equipment.


2009 ◽  
Vol 9 (7) ◽  
pp. 2413-2418 ◽  
Author(s):  
N. David ◽  
P. Alpert ◽  
H. Messer

Abstract. We propose a new technique that overcomes the obstacles of the existing methods for monitoring near-surface water vapour, by estimating humidity from data collected through existing wireless communication networks. Weather conditions and atmospheric phenomena affect the electromagnetic channel, causing attenuations to the radio signals. Thus, wireless communication networks are in effect built-in environmental monitoring facilities. The wireless microwave links, used in these networks, are widely deployed by cellular providers for backhaul communication between base stations, a few tens of meters above ground level. As a result, if all available measurements are used, the proposed method can provide moisture observations with high spatial resolution and potentially high temporal resolution. Further, the implementation cost is minimal, since the data used are already collected and saved by the cellular operators. In addition – many of these links are installed in areas where access is difficult such as orographic terrain and complex topography. As such, our method enables measurements in places that have been hard to measure in the past, or have never been measured before. The technique is restricted to weather conditions which exclude rain, fog or clouds along the propagation path. Strong winds that may cause movement of the link transmitter or receiver (or both) may also interfere with the ability to conduct accurate measurements. We present results from real-data measurements taken from two microwave links used in a backhaul cellular network that show convincing correlation to surface station humidity measurements. The measurements were taken daily in two sites, one in northern Israel (28 measurements), the other in central Israel (29 measurements). The correlation between the microwave link measurements and the humidity gauges were 0.9 and 0.82 for the north and central sites, respectively. The Root Mean Square Differences (RMSD) were 1.8 g/m3 and 3.4 g/m3 for the northern and central site measurements, respectively.


2021 ◽  
Vol 19 (2) ◽  
pp. 41-48
Author(s):  
Yu. V. Nemtsov ◽  
I. V. Seryogin ◽  
P. I. Volnov

Base station (BS) is a terminal device of a radio communication network, while railway radio communications play an important role in ensuring safety of passenger and cargo transportation.A proposed method for calculating the performance of base stations in railway digital radio communication networks is intended to calculate for the BS the probabilities of being in certain state.BS was decomposed and such functional elements as circuit groups and a radio frequency path were identified, as well as the central module ensuring the exchange of information with elements of this BS and with other BSs. A detailed study of each element has increased accuracy of the proposed method. Following the Markov model, BS is presented as a system in which all possible states are considered. Models for BS with two and three circuit groups have been constructed. The parameters of each functional element of the model can be obtained through observation over a certain period. The solution of the system of equations for each of the models presented in the article will allow obtaining the values of the system being in a certain state. The obtained characteristics can be used to calculate the reliability of the entire radio communication network, and then to assess quality of service provided to the users of this network.Conclusions are made about the possibilities of using the obtained models when designing new railway communication networks and when calculating quality indices of existing ones. The proposed models can be applied not only to railway radio communication networks but also to mobile communication networks of commercial operators. 


2018 ◽  
Vol 2018 ◽  
pp. 1-17 ◽  
Author(s):  
Michel Matalatala ◽  
Margot Deruyck ◽  
Emmeric Tanghe ◽  
Luc Martens ◽  
Wout Joseph

Massive MIMO techniques are expected to deliver significant performance gains for the future wireless communication networks by improving the spectral and the energy efficiencies. In this paper, we propose a method to optimize the positions, the coverage, and the energy consumption of the massive MIMO base stations within a suburban area in Ghent, Belgium, while meeting the low power requirements. The results reveal that massive MIMO provides better performances for the crowded scenario where users’ mobility is limited. With 256 antennas, a massive MIMO base station can simultaneously multiplex 18 users at the same time-frequency resource while consuming 8 times less power and providing 200 times more capacity than a 4G reference network for the same coverage. Moreover, a pilot reuse pattern of 3 is recommended in a multiuser multicell environment to obtain a good tradeoff between the high spectral efficiency and the low power requirement.


2021 ◽  
Author(s):  
Lilatul Ferdouse

Cellular based M2M systems generate massive number of access requests which create congestion in the cellular network. The contention-based random access procedures are designed for cellular networks which cannot accommodate a large number of M2M traffic. Moreover, M2M systems share same radio resources with cellular users. Resource allocation problem becomes a challenging issue in cellular M2M systems. In this thesis, we address these two problems by analyzing a contention-based slotted Aloha random access procedure for M2M networks using different performance metrics. The impact of massive M2M traffic over cellular traffic is studied based on different arrival rate, random access opportunity and throughput. An analytical model of selecting a base station (eNB) along with load balancing is developed. Finally, two methods have been presented and evaluated with M2M traffic. First one is dynamic access class barring method which controls RAN level congestion by selecting an appropriate eNB and applying load balancing method. Second one is relay-assisted radio resource allocation method which maximizes the sum throughput of the system by utilizing the available radio resource blocks and relay nodes to the MTC systems. Numerical results show that frame transmission rate influences the selection probability of the base stations. Moreover, the dynamic access class barring parameter along with frame transmission rate improve the overall throughput and access success probability among base stations as well as avoid overload situation in a particular base station.


Sign in / Sign up

Export Citation Format

Share Document