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Improved Metric Function for AlphaSeq Algorithm to Design Ideal Complementary Codes for Multi-Carrier CDMA Systems

Shucong TIAN, Meng YANG, Jianpeng WANG, Rui WANG, Avik R. ADHIKARY

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Summary :

AlphaSeq is a new paradigm to design sequencess with desired properties based on deep reinforcement learning (DRL). In this work, we propose a new metric function and a new reward function, to design an improved version of AlphaSeq. We show analytically and also through numerical simulations that the proposed algorithm can discover sequence sets with preferable properties faster than that of the previous algorithm.

Publication
IEICE TRANSACTIONS on Fundamentals Vol.E105-A No.5 pp.901-905
Publication Date
2022/05/01
Publicized
2021/11/15
Online ISSN
1745-1337
DOI
10.1587/transfun.2021EAL2060
Type of Manuscript
LETTER
Category
Communication Theory and Signals

Authors

Shucong TIAN
  Southwest Jiaotong University
Meng YANG
  Southwest Jiaotong University
Jianpeng WANG
  Southwest Jiaotong University
Rui WANG
  Southwest Jiaotong University
Avik R. ADHIKARY
  Southwest Jiaotong University

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