Prototyping Distributed Collision-Free MAC Protocols for WLANs in Real Hardware

AbstractFiber wireless (Fi-Wi) communication network is the amalgamation of optical and wireless access networks, which provides better bandwidth for achieving efficient data transmission. Medium access control (MAC) protocols are used in the wireless network for controlling the data flow from the transmitter to the receiver end. The delay produced by these protocols tells about the system efficiency. This paper shows a Fi-Wi system in the long-term evaluation-advanced (LTE-A) environment, which incorporates the dependency of delay generated by the specific MAC protocols during the transmission process. This paper aimed to scrutinize the effects of Carrier Sense Multiplexing Access with Collision Detection (CSMA/CD), Carrier Sense Multiplexing Access with Collision Avoidance (CSMA/CA) and Slotted ALOHA on the performance of the Fi-Wi system. Free space optical (FSO) channel is incorporated to forward the data to user end. In such system, the optical signal is multiplexed using the Orthogonal Frequency Division Multiplexing (OFDM) technique and finally the data are fetched at the receiver end and different criterions such eye-height, Q-factor and bit error rate are evaluated. Simulation results are performed using MATLAB software. The comparative analysis is also performed in terms of data transmission efficiency, delay and throughput of MAC protocols. This shows the effective results of the proposed system according to the delay produced by MAC protocols.

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A probabilistic analysis of energy efficiency of wireless sensor network duty-cycled MAC protocols

Proceedings of the 6th ACM workshop on QoS and security for wireless and mobile networks - Q2SWinet '10 ◽

10.1145/1868630.1868638 ◽

2010 ◽

Cited By ~ 2

Author(s):

Robert Abo ◽

Kamel Barkoui ◽

Hafedh Zayani

Keyword(s):

Energy Efficiency ◽

Wireless Sensor Network ◽

Sensor Network ◽

Probabilistic Analysis ◽

Mac Protocols ◽

Wireless Sensor

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Performance Analysis of Synchronous Multi-Radio Multi-Link MAC Protocols in IEEE 802.11be Extremely High Throughput WLANs

Applied Sciences ◽

10.3390/app11010317 ◽

2020 ◽

Vol 11 (1) ◽

pp. 317

Author(s):

Taewon Song ◽

Taeyoon Kim

Keyword(s):

Ieee 802.11 ◽

Markov Chain Model ◽

Careful Consideration ◽

Mac Protocols ◽

Media Access Control ◽

Chain Model ◽

Distributed Coordination ◽

Media Access ◽

Medium Access ◽

Coordination Function

The representative media access control (MAC) mechanism of IEEE 802.11 is a distributed coordination function (DCF), which operates based on carrier-sense multiple access with collision avoidance (CSMA/CA) with binary exponential backoff. The next amendment of IEEE 802.11 being developed for future Wi-Fi by the task group-be is called IEEE 802.11be, where the multi-link operation is mainly discussed when it comes to MAC layer operation. The multi-link operation discussed in IEEE 802.11be allows multi-link devices to establish multiple links and operate them simultaneously. Since the medium access on a link may affect the other links, and the conventional MAC mechanism has just taken account of a single link, the DCF should be used after careful consideration for multi-link operation. In this paper, we summarize the DCFs being reviewed to support the multi-radio multi-link operation in IEEE 802.11be and analyze their performance using the Markov chain model. Throughout the extensive performance evaluation, we summarize each MAC protocol’s pros and cons and discuss essential findings of the candidate MAC protocols.

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A real-time HIL control system on rotary inverted pendulum hardware platform based on double deep Q-network

Measurement and Control ◽

10.1177/00202940211000380 ◽

2021 ◽

Vol 54 (3-4) ◽

pp. 417-428

Author(s):

Yanyan Dai ◽

KiDong Lee ◽

SukGyu Lee

Keyword(s):

Control System ◽

Reinforcement Learning ◽

Inverted Pendulum ◽

Learning Algorithm ◽

Deep Understanding ◽

Control Engineering ◽

Experience Replay ◽

Real Hardware ◽

Rotary Inverted Pendulum ◽

Reinforcement Learning Algorithm

For real applications, rotary inverted pendulum systems have been known as the basic model in nonlinear control systems. If researchers have no deep understanding of control, it is difficult to control a rotary inverted pendulum platform using classic control engineering models, as shown in section 2.1. Therefore, without classic control theory, this paper controls the platform by training and testing reinforcement learning algorithm. Many recent achievements in reinforcement learning (RL) have become possible, but there is a lack of research to quickly test high-frequency RL algorithms using real hardware environment. In this paper, we propose a real-time Hardware-in-the-loop (HIL) control system to train and test the deep reinforcement learning algorithm from simulation to real hardware implementation. The Double Deep Q-Network (DDQN) with prioritized experience replay reinforcement learning algorithm, without a deep understanding of classical control engineering, is used to implement the agent. For the real experiment, to swing up the rotary inverted pendulum and make the pendulum smoothly move, we define 21 actions to swing up and balance the pendulum. Comparing Deep Q-Network (DQN), the DDQN with prioritized experience replay algorithm removes the overestimate of Q value and decreases the training time. Finally, this paper shows the experiment results with comparisons of classic control theory and different reinforcement learning algorithms.

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