Energy and Spectrum Efficiency Trade-off of Non-Orthogonal Multiple Access (NOMA) over OFDMA for Machine-to-Machine Communication

Selvam, K.C.; Kumar, K. Ashok

doi:10.1109/iconstem.2019.8918884

Cited by 8 publications

(3 citation statements)

References 17 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Following the present results, another method can be implemented in the system like in [76] using a trade-off situation in the system which focus on power allocation more than other function. The present findings seem to be consistent with the result, for that reason; Li and Gui [16] seems to play with a hybrid method of time division multiple access (TDMA) with NOMA in cellular which focuses on the improved time-sharing scheme while EE of the system keeps in good condition.…”

Section: Machine-to-machinementioning

confidence: 61%

Energy-efficient non-orthogonal multiple access for wireless communication system

Darus

Idris

Hashim

2023

IJECE

View full text Add to dashboard Cite

<p>Non-orthogonal multiple access (NOMA) has been recognized as a potential solution for enhancing the throughput of next-generation wireless communications. NOMA is a potential option for 5G networks due to its superiority in providing better spectrum efficiency (SE) compared to orthogonal multiple access (OMA). From the perspective of green communication, energy efficiency (EE) has become a new performance indicator. A systematic literature review is conducted to investigate the available energy efficient approach researchers have employed in NOMA. We identified 19 subcategories related to EE in NOMA out of 108 publications where 92 publications are from the IEEE website. To help the reader comprehend, a summary for each category is explained and elaborated in detail. From the literature review, it had been observed that NOMA can enhance the EE of wireless communication systems. At the end of this survey, future research particularly in machine learning algorithms such as reinforcement learning (RL) and deep reinforcement learning (DRL) for NOMA are also discussed.</p>

show abstract

Section: Machine-to-machinementioning

confidence: 61%

Energy-efficient non-orthogonal multiple access for wireless communication system

Darus

Idris

Hashim

2023

IJECE

View full text Add to dashboard Cite

show abstract

“…To share resources between users of a communication channel with the OFDMA technique, each user is assigned some orthogonal sub-channel and guard intervals are inserted between these sub-channels. As the number of users grows tremendously, these guard intervals amount significantly and result in poor spectral efficiency [3]. In addition, the trade-off between energy efficiency and data rate should be ameliorated particularly in uplink scenarios where battery saving of mobile devices is of the essence [4].…”

Section: Introductionmentioning

confidence: 99%

Development of CNN-LSTM Hybrid Deep Learning Network for the Joint Detection of Non-Orthogonal Multiple Access Signals in 5G Uplink Receivers

2022

IJIES

View full text Add to dashboard Cite

This paper presents a novel approach for signal detection in non-orthogonal multiple access (NOMA) uplink receivers. We propose converting incoming packets into a stream of 2D image-like vectors. Thereby, converting a signal detection problem into a video classification problem. Our approach is true end-to-end learning where no manual feature engineering and/or pre-processing is required. Detection is done blindly in a joint fashion with no explicit channel estimation and equalization steps required. Successive interference cancellation (SIC) is the default method for detecting NOMA packets, but it requires perfect channel estimation to be maintained. Deep learning approaches have shown great promise. However, they suffer from overfitting and/or poor performance. We show how to improve performance by a better training dataset generation procedure and hyperparameter optimization along with the use of CNN as a feature filter. The CNN-LSTM hybrid network has registered a training and testing accuracies of 88.61 and 85.36 which are higher than the state-of-the-art approaches and its symbol error rate (SER) vs signal-to-noise ratio (SNR) performance is higher by about 9dB than the LSTM approach, maximum likelihood and other standard SIC based approaches like the minimum mean square error (MMSE) and least square (LS). This suggests deep learning-based receivers as strong candidates for the upcoming generations of wireless communication systems.

show abstract

“…The Non-Orthogonal Multiple Access (NOMA) is a promising communication technique, which will satisfy the performance requirements for fifth-generation (5G) communications systems for both uplink and downlink scenarios [1][2][3][4][5]. Unlike conventional orthogonal multiple access (OMA) techniques including frequency division multiple access (FDMA), time division multiple access (TDMA), code division multiple access (CDMA) and orthogonal frequency division multiple access (OFDMA), that serve a single user in each orthogonal resource block, the NOMA can increase the number of users, improve spectrum efficiency, ensure massive connectivity, high performance, and low latency [6][7][8][9][10][11]. In downlink NOMA scenarios, all the individual information signals are superimposed on a single signal transmitted by the base station (BS) to the equipment users.…”

Section: Introductionmentioning

confidence: 99%

Bit Error Rate Analysis of NOMA-OFDM in 5G Systems With Non-Linear HPA With Memory

et al. 2021

View full text Add to dashboard Cite

The orthogonal frequency division multiplexing (OFDM) and the non-orthogonal multiple access (NOMA) scheme are presented as promising techniques to meet the requirement of fifth-generation (5G) communication systems. Although much attention has recently been devoted to study these techniques, some scenarios have still been less explored. Considering that a fundamental part of any communication system is the use of power amplifiers, this paper presents an analytical evaluation of the bit error rate (BER) of NOMA-OFDM systems in the presence of a high power amplifier (HPA) with memory. Considering that the non-linear distortions generated by the HPA can be modeled using a polynomial model with memory, new theoretical expressions are developed to obtain the BER of the system. Specifically, exact BER expressions for a downlink NOMA-OFDM system with two users are presented and verified by Monte Carlo simulation results. The obtained numerical results demonstrate that the performance degradation of both users is highly dependent on the non-linear distortions, even when the successive interference cancellation (SIC) technique is performed perfectly.INDEX TERMS 5G, bit error rate, high power amplifier, non-linearity, non-orthogonal multiple access, orthogonal frequency division multiplexing.

show abstract

Energy and Spectrum Efficiency Trade-off of Non-Orthogonal Multiple Access (NOMA) over OFDMA for Machine-to-Machine Communication

Cited by 8 publications

References 17 publications

Energy-efficient non-orthogonal multiple access for wireless communication system

Energy-efficient non-orthogonal multiple access for wireless communication system

Development of CNN-LSTM Hybrid Deep Learning Network for the Joint Detection of Non-Orthogonal Multiple Access Signals in 5G Uplink Receivers

Bit Error Rate Analysis of NOMA-OFDM in 5G Systems With Non-Linear HPA With Memory

Contact Info

Product

Resources

About