آشکارساز نزدیک به بهینه با پیچیدگی کم مبتنی بر الگوریتم آموزش-یادگیری برای سیستم چندآنتنه انبوه

نوع مقاله : مقاله پژوهشی

نویسندگان

1 دانشکده مهندسی برق، دانشگاه صنعتی شریف، تهران، ایران.

2 دانشکده مهندسی برق و کامپیوتر، دانشگاه صنعتی نوشیروانی بابل، بابل، ایران

چکیده

با وجود مزایای فنّاوری چندآنتنه انبوه، الگوریتم‌های آشکارساز سنتی چندآنتنه برای سیستم‌ها با آنتن‌های مقیاس بزرگ مناسب نیستند و به‌کارگیری این فنّاوری مستلزم افزایش چشمگیر هزینه‌های محاسباتی می‌باشد. در این مقاله، یک گیرنده با پیچیدگی کم با استفاده از الگوریتم فراابتکاری آموزش-یادگیری (TLBO) برای سیستم چندآنتنه انبوه طراحی می‌گردد. الگوریتم TLBO به عنوان یکی از روش‌های پیشرفته هوش جمعی، برای مسئله بهینه‌سازی عددی با مقیاس بزرگ بسیار کاربردی است؛ بنابراین، ما ازاین‌روش برای جستجوی بردار راه حل بهینه در الفبای مدولاسیون استفاده می‌کنیم. به جهت اثبات صحت و کارایی آشکارساز پیشنهادی شبیه‌سازی سیستم با ابعاد متفاوتی از 64×64 تا 1024×1024 انجام گردید. آشکارساز TLBO پیشنهادی در مدت زمان محدود، به میزان خطای بیت نزدیک به10^(-5) در نسبت متوسط سیگنال به نویز دریافتی 12 ‌دسی‌بل دست می‌یابد که تقریباً برابر با عملکرد خطای بیت آشکارساز بهینه، درست‌نمایی بیشینه، است. در نتیجه آشکارساز پیشنهادی برای به‌کارگیری در سیستم‌های چندآنتنه انبوه بسیار کارا می‌باشد.

کلیدواژه‌ها

موضوعات

عنوان مقاله [English]

A Low Complexity Near-Optimal Detector Based on Teaching-Learning Algorithm for Massive MIMO

نویسندگان [English]

  • Hamid Amiriara 1
  • Mohammadreza Zahabi 2
1 Electrical Engineering, Sharif University of Technology, Tehran, Iran.
2 Faculty of Electrical and Computer Engineering, Babol Noshirvani University of Technology, Babol, Iran
چکیده [English]

Despite the advantages of massive multi-input multi-output (MIMO) technology, traditional multi-antenna detection algorithms are not suitable for systems with large-scale antennas, and the use of this technology requires a significant increase in computational costs. In this paper, a low-complexity receiver is proposed using a Teaching-Learning based optimization (TLBO) heuristic algorithm for a large-scale system. The TLBO algorithm, as one of the advanced methods of intelligence, is very useful for large-scale problems. Therefore, we use this method to search for the optimal solution vector in the modulation alphabet. In order to prove the accuracy and efficiency of the detector, it was suggested to simulate the system with different dimensions from 64×64 to 1024×1024. The proposed TLBO detector, in a limited time, achieves a bit error rate (BER) 10^(-5) in the average signal-to-noise ratio of 12 dB, which is approximately equal to the optimal detector performance, and maximum likelihood. As a result, the proposed detector is very efficient for use in massive MIMO systems.

کلیدواژه‌ها [English]

  • 5G wireless communication
  • Detection algorithm
  • Massive Multi Input Multi Output
  • Teaching-Learning based optimization

مراجع

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