14480

مروري بر دسترسي چندگانه تقسيم پرتو (BDMA) در شبكه‌هاي تلفن همراه 5G با استفاده از تكنيك‌هاي اكولايزرهاي يادگيري عميق

1402

دكتر ابوالفضل ديانت

دكتر ناصر مزينى

With the rising interest for high velocity data flow and the rising number of clients of mobile networks, virtual entertainment, and the Web. Consequently, current innovation, for example, 3.5G and 4G can't uphold this immense expansion in that frame of mind of clients and data and thus the earnest need to foster the future (5G) mobile network. 5G correspondences frameworks are expected to give much preferred execution over 4G frameworks as far as data flow rate, coverage, interference suppression, capacity, cost, power utilization, and access time. 5G correspondences innovation has accomplished critical upgrades in the space of range, transmission capacity, power, signal proficiency, and cost. In the previous ten years, multiple info multiple result (MIMO) frameworks have become one of the key advancements that give higher ghastly effectiveness to high-goal data transmission and gathering. Beam advancements accompanied the new Beam Division Multiple Access (BDMA) innovation for the fifth generation network to build the productivity of MIMO innovation and safeguard the beam and energy from being lost. The proposed model is intended to simulate the transmission of a gathering of clients over a covering remote Gaussian transmission channel, with the goal that every client is designated a particular transporter recurrence of (1200, 1000, 800) MHz, separately. The utilization of the created versatile equalizer framework has additionally been applied, which deals with speculating attributes to smother noise and interference waves, limit and kill their effect on the sent signal implanted through remote correspondence channels. By executing reproduction programs and frameworks planned as per standard principles and controls, to remove client data signals utilizing the updated Deep Learning equalizer framework, it is trusted that the blunder rate results will be low with a signal-to-noise ratio (SNR) for the transmission of 5 dB, and the gathering exactness will be worked on by over 95%.

12/11/2024 12:00:00 AM

85813

1403/11/23

A REVIEW OF BEAM DIVISION MULTIPLE ACCESS (BDMA)IN 5G MOBILE NETWORKS USING DEEP LEARNING EQUALIZERS TECHNIQUES

سيستم هاي اكولايزر يادگيري عميق , مولتي پلكسينگ تقسيم فركانس متعامد (OFDM) , مدولاسيون ديجيتال , چند ورودي-چند خروجي (MIMO) , دسترسي چندگانه تقسيم پرتو (BDMA) , توان عملياتي , نرخ خطاي بيت (BER) , تأخير

Deep Learning Equalizers Systems , Orthogonal Frequency Division Multiplexing (OFDM) , Digital Modulation , Multi-Input-Multi-Output (MIMO) , Beam Division Multiple Access (BDMA) , Throughput , Bit Error Rate (BER) , Delay (Latency)