scholarly journals Uplink Transmit Power Control for Single-Carrier Grouped FDMA with Iterative Multiuser Detection

2019 ◽  
Vol 10 (1) ◽  
pp. 119
Author(s):  
Yong-Sang Cho ◽  
Yun-Seong Kang ◽  
Moonsik Min

We consider an uplink power allocation scheme for single-carrier frequency-division multiple access (FDMA) with iterative multiuser detection, called single-carrier grouped FDMA (SC-GFDMA). SC-GFDMA is a non-orthogonal scheme in which several users share a single time-frequency resource. Hence, the uplink signal of a user can be regarded as both a signal and a source of interference. The signal power of each user should be sufficiently high to ensure reliable signal detection and sufficiently low to suppress inter-user interference. That is, the transmit power of each user should be adjusted appropriately to achieve high spectral efficiency. In this context, a power control method for an uplink SC-GFDMA system is proposed by analyzing the signal-to-interference-plus-noise ratios of users sharing each time-frequency resource. In particular, the uplink spectral efficiency is improved by limiting the transmit power of each user according to a criterion derived using a semi-analytic method called signal-to-noise ratio-variance density evolution. Simulation results demonstrate that the proposed method can significantly increase the spectral efficiency of the system, even with a considerably reduced total transmit power.

Energies ◽  
2019 ◽  
Vol 12 (17) ◽  
pp. 3234
Author(s):  
Jingon Joung ◽  
Han Lim Lee ◽  
Jian Zhao ◽  
Xin Kang

In this paper, a power control method is proposed for a buffer-aided relay node (RN) to enhance the energy efficiency of the RN system. By virtue of a buffer, the RN can reserve the data at the buffer when the the channel gain between an RN and a destination node (DN) is weaker than that between SN and RN. The RN then opportunistically forward the reserved data in the buffer according to channel condition between the RN and the DN. By exploiting the buffer, RN reduces transmit power when it reduces the transmit data rate and reserve the data in the buffer. Therefore, without any total throughput reduction, the power consumption of RN can be reduced, resulting in the energy efficiency (EE) improvement of the RN system. Furthermore, for the power control, we devise a simple power control method based on a two-dimensional surface fitting model of an optimal transmit power of RN. The proposed RN power control method is readily and locally implementable at the RN, and it can significantly improve EE of the RN compared to the fixed power control method and the spectral efficiency based method as verified by the rigorous numerical results.


2010 ◽  
Vol 48 (3) ◽  
pp. 164-171 ◽  
Author(s):  
Tae-Won Yune ◽  
Chan-Ho Choi ◽  
Gi-Hong Im ◽  
Jong-Bu Lim ◽  
Eung-Sun Kim ◽  
...  

Electronics ◽  
2020 ◽  
Vol 9 (10) ◽  
pp. 1606
Author(s):  
Donghyeon Kim ◽  
In-Ho Lee

The proximity-based device-to-device (D2D) communication allows for internet of things, public safety, and data offloading services. Because of these advantages, D2D communication has been applied to wireless communication networks. In wireless networks using D2D communication, there are challenging problems of the data rate shortage and coverage limitation due to co-channel interference in the proximity communication. To resolve the problems, transmit power control schemes that are based on deep learning have been presented in network-assisted D2D communication systems. The power control schemes have focused on enhancing spectral efficiency and energy efficiency in the presence of interference. However, the data-rate fairness performance may be a key performance metric in D2D communications, because devices in proximity can expect fair quality of service in the system. Hence, in this paper, a transmit power control scheme using a deep-learning algorithm based on convolutional neural network (CNN) is proposed to consider the data-rate fairness performance in network-assisted D2D communication systems, where the wireless channels are modelled by path loss and Nakagami fading. In the proposed scheme, the batch normalization (BN) scheme is introduced in order to further enhance the spectral efficiency of the conventional deep-learning transmit power control scheme. In addition, a loss function for the deep-learning optimization is defined in order to consider both the data-rate fairness and spectral efficiency. Through simulation, we show that the proposed scheme can achieve extremely high fairness performance while improving the spectral efficiency of the conventional schemes. It is also shown that the improvement in the fairness and spectral efficiency is achieved for different Nakagami fading conditions and sizes of area containing the devices.


2021 ◽  
Vol 2134 (1) ◽  
pp. 012023
Author(s):  
Ya. V. Kryukov ◽  
D. A. Pokamestov ◽  
R. R. Abenov ◽  
S. M. Mukhamadiev ◽  
I. Kanatbekuli

Abstract Non-orthogonal multiple access (NOMA) is a promising user multiplexing technique for future wireless networks that allows increasing their spectral efficiency (SE). Power-Domain NOMA (PD-NOMA) is one of the most perspective techniques in the NOMA group. It makes it possible to perform the transmission of information symbols of several users within the same time-frequency resource segment (RS) without a spreading code. Many research works show the high efficiency of PD-NOMA compared to the orthogonal multiple access (OMA). However, these results are obtained analytically using Shannon’s formula and not taking into account the real performance of existing modulation and coding schemes (MCS). The issue is that it is impossible to obtain the achievable practical performance of PD-NOMA systems in this way. We obtain the SE in RS of a PD-NOMA system with Long Term Evolution (LTE) MCS’s and compare it with OMA. As a result, we conclude that PD-NOMA gains the system SE when the multiplexed user’s signal-to-noise ratio (SNR) outreaches the threshold of the highest performing MCS provided for the transmission by a MCS table.


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