Deep learning based NOMA in IoT

We need to generate random binary bits of 1024 length and do rate 1/2 convolution encoding and do the BPSK modulation and pass it through a noisy channel and decoding it with LSTM( long short term memory).

We need to get the output same as the applied input.

Medium Access Protocols involves a broader spectrum (up to 60 GHz) and will allow for

non-orthogonal techniques and most likely be OFDMA-based. Nonetheless, there is a

consensus in the literature that the orthogonal multiple access approach will not suffice

to support the massive access from a vast number of loT systems devices. That is

because grant-based communications suffer from collision rates over the random-

access channel that is as high as 10%, for less than ten active users. Moreover, the

signalling overhead involved in establishing a link is about 30- 50% of the payload size,

for messages less than 200 bits long. In terms of latency, the grant-based access

procedure in LTE-A, for example, takes around 5-8 ms in the best-case scenario. Thus,

grant-based access fails at meeting many KPIs when massive connectivity is required for

short packet transmissions. Because of this, the light-weight random access protocols

were heavily investigated over the past years. The throughput has improved in orders

of magnitude with sophisticated yet still low-complex transceiver algorithms.

In this project, we will look into whether we can adopt the advanced deep learning

technology in solving this issue, and design low-complexity transmitter and receiver to

allow multiple sensors to transmit short packets simultaneously in the network. The

student for this project should be self-motivated and willing to read the existing

literature. The student should be good at mathematics and interested in modelling

physical systems using mathematical models. The student should possess strong

programming skills in Python with the knowledge of Tensorflow or Pytorch. Critical

thinking ability, problem-solving skills, and willing to try are essential.

Skills: Matlab and Mathematica, Python

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About the Employer:
( 1 review ) Cairns, Australia

Project ID: #32251473

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Professional Mathematician and master in Matlab️ Hello , I hope you are safe and Doing well I have seen your project requirements , I am looking to discuss further with you Hope we will meet soon to discuss further More

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Expert in Matlab, Simulink, Communication System, Signal Processing, Image Processing Artificial Intelligence. Excellent in Electrical Engg. Algorithms, OFDM, Tx, Rx, Channel, AWGN, Raleigh, PAPR, CCDF. Already done si More

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- previous experience in such topics ; - degree stats -maths ; - eager to discuss a lot in this chat stream ;

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Matlab and Mathematica, Python skilled professional with over 5 years of expertise. Can deliver on the expected lines as needed in the defined timelines. Thanks.

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The student should possess strong programming skills in Python with the knowledge of Tensorflow or Pytorch. Critical thinking ability, problem-solving skills, and willing to try are essential. Assalam-o-Alaikum ⭐⭐⭐Hi More

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