scholarly journals An Improved Sarsa($\lambda$ ) Reinforcement Learning Algorithm for Wireless Communication Systems

IEEE Access ◽  
2019 ◽  
Vol 7 ◽  
pp. 115418-115427 ◽  
Author(s):  
Hao Jiang ◽  
Renjie Gui ◽  
Zhen Chen ◽  
Liang Wu ◽  
Jian Dang ◽  
...  
2021 ◽  
Vol 19 (2) ◽  
pp. 2056-2094
Author(s):  
Koji Oshima ◽  
◽  
Daisuke Yamamoto ◽  
Atsuhiro Yumoto ◽  
Song-Ju Kim ◽  
...  

<abstract><p>Data-driven and feedback cycle-based approaches are necessary to optimize the performance of modern complex wireless communication systems. Machine learning technologies can provide solutions for these requirements. This study shows a comprehensive framework of optimizing wireless communication systems and proposes two optimal decision schemes that have not been well-investigated in existing research. The first one is supervised learning modeling and optimal decision making by optimization, and the second is a simple and implementable reinforcement learning algorithm. The proposed schemes were verified through real-world experiments and computer simulations, which revealed the necessity and validity of this research.</p></abstract>


Author(s):  
A. Suresh Babu ◽  
B. Anand

: A Linear Feedback Shift Register (LFSR) considers a linear function typically an XOR operation of the previous state as an input to the current state. This paper describes in detail the recent Wireless Communication Systems (WCS) and techniques related to LFSR. Cryptographic methods and reconfigurable computing are two different applications used in the proposed shift register with improved speed and decreased power consumption. Comparing with the existing individual applications, the proposed shift register obtained >15 to <=45% of decreased power consumption with 30% of reduced coverage area. Hence this proposed low power high speed LFSR design suits for various low power high speed applications, for example wireless communication. The entire design architecture is simulated and verified in VHDL language. To synthesis a standard cell library of 0.7um CMOS is used. A custom design tool has been developed for measuring the power. From the results, it is obtained that the cryptographic efficiency is improved regarding time and complexity comparing with the existing algorithms. Hence, the proposed LFSR architecture can be used for any wireless applications due to parallel processing, multiple access and cryptographic methods.


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