Applications of Hybrid Intelligent Systems in Adaptive Communication

2018 ◽  
pp. 1139-1173
Author(s):  
Atta ur Rahman
Keyword(s):  
Intelligent Systems ◽  
Orthogonal Frequency Division Multiplexing ◽  
Code Rate ◽  
Throughput Maximization ◽  
System Throughput ◽  
Rule Base ◽  
Modulation Scheme ◽  
Base System ◽  
Transmission Parameters ◽  
Adaptive Power

Dynamic allocation of the resources for optimum utilization and throughput maximization is one of the most important fields of research nowadays. In this process the available resources are allocated in such a way that they are maximally utilized to enhance the overall system throughput. In this chapter a similar problem is approached which is found in Orthogonal Frequency Division Multiplexing (OFDM) environment, in which the transmission parameters namely the code rate, modulation scheme and power are adapted in such a way that overall system's data rate is maximized with a constrained bit error rate and transmit power. A Fuzzy Rule Base System (FRBS) is proposed for adapting the code rate and modulation scheme while Genetic Algorithm (GA) and Differential Evolution (DE) algorithm are used for adaptive power allocation. The proposed scheme is compared with other schemes in the literature including the famous Water-filling technique which is considered as a benchmark in the adaptive loading paradigm. Supremacy of the proposed technique is shown through computer simulations.

Applications of Hybrid Intelligent Systems in Adaptive Communication

2018 ◽  
pp. 183-217 ◽  
Author(s):  
Atta ur Rahman
Keyword(s):  
Intelligent Systems ◽  
Orthogonal Frequency Division Multiplexing ◽  
Code Rate ◽  
Throughput Maximization ◽  
System Throughput ◽  
Rule Base ◽  
Modulation Scheme ◽  
Base System ◽  
Transmission Parameters ◽  
Adaptive Power

Dynamic allocation of the resources for optimum utilization and throughput maximization is one of the most important fields of research nowadays. In this process the available resources are allocated in such a way that they are maximally utilized to enhance the overall system throughput. In this chapter a similar problem is approached which is found in Orthogonal Frequency Division Multiplexing (OFDM) environment, in which the transmission parameters namely the code rate, modulation scheme and power are adapted in such a way that overall system's data rate is maximized with a constrained bit error rate and transmit power. A Fuzzy Rule Base System (FRBS) is proposed for adapting the code rate and modulation scheme while Genetic Algorithm (GA) and Differential Evolution (DE) algorithm are used for adaptive power allocation. The proposed scheme is compared with other schemes in the literature including the famous Water-filling technique which is considered as a benchmark in the adaptive loading paradigm. Supremacy of the proposed technique is shown through computer simulations.

Optimized-Fuzzy-Logic-Based Bit Loading Algorithms

2017 ◽  
pp. 305-315
Author(s):  
Sankar Ganesh S. ◽  
Mohanaprasad K. ◽  
Arunprakash Jayaprakash ◽  
Sivanantham Sathasivam
Keyword(s):  
Fuzzy Logic ◽  
Communication Systems ◽  
Orthogonal Frequency Division Multiplexing ◽  
Adaptive Modulation ◽  
Optimal Solution ◽  
System Throughput ◽  
Bit Loading ◽  
Minimum Number ◽  
Adaptive Power ◽  
Number Of Iterations

Next generation wireless communication systems promise the subscribers with Giga-bit-data-rate experience at low Bit Error Rate (BER) under adverse channel conditions. In order to maximize the overall system throughput of Orthogonal Frequency Division Multiplexing (OFDM), adaptive modulation is one of the key solutions. In adaptive modulated OFDM, the subcarriers are allocated with data bits and energy in accordance with the Signal to Interference Ratio (SIR) of the multipath channel, which is referred to as adaptive bit loading and adaptive power allocation respectively. The number of iterations required allocating the target bits and energy to a sub channel is optimized. The key choice of the paper is to allocate the bits with minimum number of iterations after clustering the sub channels using fuzzy logic. The proposed method exhibits a faster convergence in obtaining the optimal solution.

МЕТОД ГЛУБОКОГО ОБУЧЕНИЯ С ПОДКРЕПЛЕНИЕМ ДЛЯ СИСТЕМ ИНТЕРНЕТА ВЕЩЕЙ НА БАЗЕ ТЕХНОЛОГИИ LORA С ОГРАНИЧЕННЫМИ РЕСУРСАМИ И ПОДДЕРЖКОЙ QoS

2021 ◽  
Author(s):  
 M.S. MUTHANNA ◽  
A.S. MUTHANNA ◽  
 A.S. BORODIN
Keyword(s):  
Data Transmission ◽  
Environmental Parameters ◽  
Code Rate ◽  
Frame Structure ◽  
Signal Quality ◽  
High Quality ◽  
Spreading Factor ◽  
Transmission Parameters ◽  
Factor Code

Achieving high Quality of Service (QoS) remains a challenge for LoRa technology. However, high QoS can be achieved via optimizing the transmission policy parameters such as bandwidth and code rate. Existing approaches do not provide an opportunity to optimize the LoRa networks' data transmission parameters. The article proposes transmission policy enforcementfor QoS-aware LoRanetworks.The QoSparameter ranking is implemented for IoT nodes where priority and nonpriority information is identified by the new field of LoRa frame structure(QRank).The optimaltransmissionpolicyenforcement uses fast deep reinforcement learning that utilizes the environmental parameters including QRank, signal quality, and signal-to-interference-plus-noise-ratio. The transmission policy is optimized for spreading factor, code rate, bandwidth, and carrier frequency. Performance evaluation is implemented using an NS3.26 LoRaWAN module. The performance is examined for various metrics such as delay and throughput. Достижение высокого качества обслуживания (QoS) по-прежнему остается достаточно сложной задачей для технологии LoRa. В принципе высокий уровень QoS может быть достигнут за счет оптимизации параметров передачи, например, пропускной способности и скорости передачи информации в сети. Известные на сегодняшний день решения не дают возможности оптимизировать параметры передачи данных для сетей LoRa. В статье предложен эффективный метод передачи данных, обеспечивающий требования по QoS при использовании технологии LoRa. Ранжирование параметров QoS для узлов интернета вещей определяется новым полем структуры фрейма LoRa (QRank) для приоритетной и неприоритетной информации. Для обеспечения эффективной передачи применяется быстрое глубокое обучение с подкреплением, для которого используются как параметры качества обслуживания, так и отношение сигнал/шум. Метод передачи оптимизирован с учетом коэффициента распространения, скорости передачи данных, полосы пропускания и несущей частоты. Оценка производительности при применении предложенного метода проведена с использованием модуля LoRaWAN в пакете имитационного моделирования NS3.26. Производительность оценивается на основе параметров задержки и пропускной способности.

scholarly journals Orthogonal Time Sequency Multiplexing Modulation

2021 ◽  
Author(s):  
Tharaj Thaj ◽  
Emanuele Viterbo
Keyword(s):  
Time Domain ◽  
Orthogonal Frequency Division Multiplexing ◽  
High Performance ◽  
High Mobility ◽  
Low Complexity ◽  
Modulation Scheme ◽  
Frequency Space ◽  
Time Frequency ◽  
Single Carrier ◽  
The Time Domain

This paper proposes <i>orthogonal time sequency multiplexing</i> (OTSM), a novel single carrier modulation scheme based on the well known Walsh-Hadamard transform (WHT) combined with row-column interleaving, and zero padding (ZP) between blocks in the time-domain. The information symbols in OTSM are multiplexed in the delay and sequency domain using a cascade of time-division and Walsh-Hadamard (sequency) multiplexing. By using the WHT for transmission and reception, the modulation and demodulation steps do not require any complex multiplications. We then propose two low-complexity detectors: (i) a simpler non-iterative detector based on a single tap minimum mean square time-frequency domain equalizer and (ii) an iterative time-domain detector. We demonstrate, via numerical simulations, that the proposed modulation scheme offers high performance gains over orthogonal frequency division multiplexing (OFDM) and exhibits the same performance of orthogonal time frequency space (OTFS) modulation, but with lower complexity. In proposing OTSM, along with simple detection schemes, we offer the lowest complexity solution to achieving reliable communication in high mobility wireless channels, as compared to the available schemes published so far in the literature.

Provide A Method Based on Genetic Algorithm to Optimize the Fuzzy Logic Controller for the Inverted Pendulum

2021 ◽  
Author(s):  
Shahrooz Alimoradpour ◽  
Mahnaz Rafie ◽  
Bahareh Ahmadzadeh
Keyword(s):  
Genetic Algorithm ◽  
Fuzzy System ◽  
Inverted Pendulum ◽  
Fuzzy Logic Controller ◽  
Fuzzy Controller ◽  
Fuzzy Rule ◽  
Rule Base ◽  
Base System ◽  
Control Rules ◽  
Dynamics And Control

Abstract One of the classic systems in dynamics and control is the inverted pendulum, which is known as one of the topics in control engineering due to its properties such as nonlinearity and inherent instability. Different approaches are available to facilitate and automate the design of fuzzy control rules and their associated membership functions. Recently, different approaches have been developed to find the optimal fuzzy rule base system using genetic algorithm. The purpose of the proposed method is to set fuzzy rules and their membership function and the length of the learning process based on the use of a genetic algorithm. The results of the proposed method show that applying the integration of a genetic algorithm along with Mamdani fuzzy system can provide a suitable fuzzy controller to solve the problem of inverse pendulum control. The proposed method shows higher equilibrium speed and equilibrium quality compared to static fuzzy controllers without optimization. Using a fuzzy system in a dynamic inverted pendulum environment has better results compared to definite systems, and in addition, the optimization of the control parameters increases the quality of this model even beyond the simple case.

Cross-Layer Optimization and Link Adaptation in Cognitive Radios

2015 ◽  
pp. 680-710
Author(s):  
Ali H. Mahdi ◽  
Mohamed A. Kalil
Keyword(s):  
Open Systems ◽  
Link Adaptation ◽  
Radio Spectrum ◽  
Modulation Scheme ◽  
Operating Parameters ◽  
Spectrum Utilization ◽  
Smart Systems ◽  
Network Layers ◽  
Transmission Parameters ◽  
Open Systems Interconnection

Cognitive Radio (CR) systems are smart systems capable of sensing the surrounding radio environment and adapting their operating parameters in order to efficiently utilize the available radio spectrum. To reach this goal, different transmission parameters across the Open Systems Interconnection (OSI) layers, such as transmit power, modulation scheme, and packet length, should be optimized. This chapter discusses the Adaptive Discrete Particle Swarm Optimization (ADPSO) algorithm as an efficient algorithm for optimizing and adapting CR operating parameters from physical, MAC, and network layers. In addition, the authors present two extensions for the proposed algorithm. The first one is Automatic Repeat reQuest-ADPSO (ARQ-ADPSO) for efficient spectrum utilization. The second one is merging ARQ-ADPSO and Case-Based Reasoning (CBR) algorithms for autonomous link adaptation under dynamic radio environment. The simulation results show improvements in the convergence time, signaling overhead, and spectrum utilization compared to the well-known optimization algorithms such as the Genetic Algorithm (GA).

QoS-Constrained Resource Allocation Scheduling for LTE Network

2015 ◽  
Vol 4 (1) ◽  
pp. 1-15 ◽  
Author(s):  
Hung-Chin Jang ◽  
Yun-Jun Lee
Keyword(s):  
Resource Allocation ◽  
Data Transmission ◽  
Orthogonal Frequency Division Multiplexing ◽  
Transmission Rate ◽  
High Mobility ◽  
System Throughput ◽  
Frequency Division ◽  
High Data ◽  
Single Carrier ◽  
Allocation Method

The goal of LTE (Long Term Evolution) is to provide high data transmission rate, scalable bandwidth, low latency, high-mobility, etc. LTE employs OFDM (Orthogonal Frequency Division Multiplexing) and SC-FDMA (Single Carrier - Frequency Division Multiple Access) for downlink and uplink data transmission, respectively. As to SC-FDMA, there are two constraints in doing resource allocation. First, the allocated resource blocks (RBs) should be contiguous. Second, those of the allocated RBs are forced to use the same modulation technique. The aim of this research is to propose a QoS-constraint resource allocation scheduling to enhance data transmission for uplink SC-FDMA. The proposed scheduling is a three-stage approach. In the first stage, it uses a time domain scheduler to differentiate user equipment (UE) services according to their distinct QoS service requirements. In the second stage, it uses a frequency domain scheduler to prioritize UE services based on channel quality. In the third stage, it limits the number of times of modulation downgrade of RBs allocation in order to enhance system throughput. In the simulations, the proposed method is compared to fixed sub-carrier dynamic resource allocation method and adaptive dynamic sub-carrier resource allocation method. Simulation results show that the proposed method outperforms the other two methods in terms of throughput, transmission delay, packet loss ratio, and RB utilization.

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