Research on Channel Power Allocation of Fog Wireless Access Network Based on NOMA

Abstract

With the developing of the smart mobile terminal and wideband application in the mobile Internet, the requirement of large capacity, low latency, and high scalability in the future network is becoming more and more stringent. Edge computing is attracting great attention to decrease time delay and improve the quality of networks' service. By integrating fog computing with the radio access network (RAN) and taking full advantage of the edge computing, fog RAN (F-RAN) is expected as a promising example for 5G/6G systems. The idea of NOMA is to distinguish users whose information is multiplexed into the same orthogonal resource by different power factors, and successive interference cancellation (SIC) is used to detect information at the fog access nodes. In this paper, we focus on dynamic power allocation of wireless sub-channel in NOMA and extend it to F-RAN. A three-user multiplexing model of a NOMA multiuser system model is developed at the transmitting side and the corresponding SIC receiver is designed. Moreover, a group of dynamic power adjusting factors is defined according to users' channel conditions, and an improved fractional transmit power allocation (I-FTPA) algorithm is proposed for NOMA and applied to the three-user model. The experimental results demonstrate that the I-FTPA performs better than the previous FPA and FTPA, more meaningful is that more than one wireless channel power allocation schemes can be found performing better than OFDMA under the same conditions for F-RAN by using the I-FTPA, which provides some significance for deploying NOMA into F-RAN in the future application. INDEX TERMS Edge computing, F-RAN, NOMA, dynamic power allocation, I-FTPA.

QoS-Driven Resource Optimization for Intelligent Fog Radio Access Network: A Dynamic Power Allocation Perspective

“…To address the nonconvex objective function in (8), we utilize the continuous smooth log-function to approximate the l 0 -norm function as [13]…”

“…Different from [6], the authors in [7] optimized the caching strategy in both the RRHs and mobile users, aiming to optimize the STP. The power allocation of the Fog-RAN was studied in [8]- [11]. In [8], the authors proposed using the nonorthogonal multiple access (NOMA) technique to distinguish multiple users in the Fog-RAN.…”

“…The power allocation of the Fog-RAN was studied in [8]- [11]. In [8], the authors proposed using the nonorthogonal multiple access (NOMA) technique to distinguish multiple users in the Fog-RAN. An improved fractional transmit power allocation algorithm was developed for the three-user NOMA-assisted Fog-RAN system.…”

On The Selection of Power Allocation Strategy in Power Domain Non‐Orthogonal Multiple Access (PD‐NOMA) for 6G and Beyond

“…Additional DPA strategic design methods were introduced in the last two years to enhance the performance of the previous DPA strategies. Improved fractional transmit power allocation (IFTPA) introduced and compared with FTPA in the work of Bai et al, 33 which allow independent power control parameter per user in NOMA‐based multicarrier system. Tao et al 23 introduced a modified version of GRPA called improved fractional strategy power allocation (IFSPA) and compared it with GRPA from the sum‐rate capacity point of view.…”

Energy-Efficient Power Allocation for Imperfect Csi Downlink Noma System

“…By 2030, the density of the connected devices is expected to reach 10 7 devices/km 2 , and multimedia applications will be the most popular applications for the users, such as mobile video calls, streaming videos, and online games. As a result, the required data rate will raise about 10 times more than that in 4G, and the peak transmitted data in the 5G is expected to be about 20 Gbps [3,4]. On the other hand, the spectrum efficiency and the energy efficiency should be degraded in 5G by x5 and x100 times, respectively [4].…”