Analysis of Power Allocation for NOMA-Based D2D Communications Using GADIA
Abstract
:1. Introduction
- 1.
- The 5G main techniques (i.e., eMBB, mMTC, URLLC) are introduced, which act as different services in various 5G applications.
- 2.
- The requirements of the future application and the fundamental open problems toward the design of NOMA-based RAN are briefly explained.
- 3.
- An overview of the new generation of radio access technology is conducted, i.e., NOMA. Further, the basic principles of NOMA, including superposition coding (SC) and successive interference cancellation (SIC) for downlink channels, are presented.
- 4.
- Considering NOMA, we propose a novel algorithm where the downlink results are combined with D2D mode and utilize Greedy Asynchronous Distributed Interference Avoidance Algorithm (GADIA) to establish two different application scenarios. Mainly, we analyze the max–min fairness optimization problem for a given fairness index in the network. The proposed optimization framework has been proven theoretically and confirmed numerically by comparing with Monte Carlo simulations for the same system model as the one introduced in [15].To the best of our knowledge, NOMA-based D2D is a device group on the max–min fairness optimization problem that was not yet studied in the context of the heterogeneous network where both the cellular and D2D devices are active.
2. Related Work
3. 5G Overview
3.1. Enhanced Mobile Broadband (eMBB)
3.2. Massive Machine Type Communication (mMTC)
3.3. URLLC
3.4. Challenges and Research Directions
4. Principle of NOMA System
4.1. SIC Technology
4.2. Resource Allocation
4.3. Principle of Transceiver
- Transmit Power: in regards to downlink NOMA, the users’ transmit power in uplink NOMA does not have to be different. It is based on the channel conditions of each user. If the users’ channel conditions are considerably different, their received SINR can be somewhat different at the BS, irrespective of their transmit Power.
- SIC Operations: the uplink NOMA and downlink NOMA users’ SIC operations and interference are also somewhat different. In particular, as displayed in Figure 6c for downlink NOMA, the signal of user n is disinfected from the interference caused by user m. In precise, that is performed by first detecting the more powerful signal of user m, modulating it and then deducting it from the composite signal. That implies SIC operation is carried out on a strong user in the downlink for cancelling the weak user’s interference. By contrast, SIC is performed at the BS in uplink NOMA to distinguish the strong user n first by treating User m as interference, as presented in Figure 6b. Then it demodulates the recovered signal and subtracts the interference imposed by user n to identify user m.
5. Proposed Algorithm
5.1. System Model
5.2. Algorithm Design
5.3. Energy Model
6. Results and Discussion
6.1. Comparison NOMA vs. OFDMA
6.2. D2D System Model
7. Conclusions and Future work
Author Contributions
Funding
Data Availability Statement
Acknowledgments
Conflicts of Interest
Sample Availability
Abbreviations
Base station. | |
Bandwidth of system. | |
Users/Terminals. | |
The number of sub-channel. | |
The number of user. | |
The power at base station. | |
Bandwidth of the sub-channle v. | |
The power of the user at the sub-channel v. | |
The signal sent by BS. | |
The modulated symbol of the ith user. | |
The received signal of the jth user at the sub-channel v. | |
The coefficient of the sub-channel v from to the jth user. | |
Additive white Gaussian noise with mean of 0 and variance of . | |
The base station transmit power. | |
is the power allocation factor for the power allocation factor. | |
represents the received Gaussian white noise. | |
indicates the channel from the base station to . | |
W | is the transmission bandwidth. |
J | is the fairness index. |
is the target fairness index in the network. | |
energy efficiency. | |
is the power consumed by the signal transmission. | |
is the power consumed due to other hardware and signal processing operations. |
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Generation | The Key Technologies | Services |
---|---|---|
1G | AMPS | Analog voice service |
2G | GSM, TDMA, CDMA | Digital voice service |
3G | WCDMA, CDMA2000, TD-SCDMA, WiMAX | Simultaneous transmission of voice and data |
4G | TD-LTE, FDD-LTE | Fast transmission of voice, data, video, image. |
5G | Millimeter Wave, Massive MIMO, Micro Base Station, D2D, Beamforming, NOMA | HD video, smart home, etc |
NOMA Use Case | Opportunities | Challenges and Research Directions |
---|---|---|
eMBB | Downlink NOMA, D2D NOMA, edge caching, Better spectral efficiency and user’s fairness, Increased number of several users satisfying their QoS | Design a comprehensive RRA, IM, caching placement and strategy that includes down-link NOMA and D2D NOMA |
mMTC | Grant-free NOMA in the uplink transmissions, Reduced energy consumed in signaling, Higher transmission success probabilities compared to OMA | Optimize the number of multiplexed users through NOMA |
URLLC | Dowanlink NOMA by increasing the networking availability, Up link NOMA by reduce the collision, Data storage and computation at the network edge | Analyze the joint provision of high reliability and low latency |
Type | Urban | Rural |
---|---|---|
BS Sensitivity (dBm) | −100 | −100 |
BS Coverage Area | 1 km | 1 km |
UEs Max Tx Power | 30 dBm | 30 dBm |
Path Loss Exponent | 6 | 2 |
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Rajab, H.; Benkhelifa, F.; Cinkler, T. Analysis of Power Allocation for NOMA-Based D2D Communications Using GADIA. Information 2021, 12, 510. https://doi.org/10.3390/info12120510
Rajab H, Benkhelifa F, Cinkler T. Analysis of Power Allocation for NOMA-Based D2D Communications Using GADIA. Information. 2021; 12(12):510. https://doi.org/10.3390/info12120510
Chicago/Turabian StyleRajab, Husam, Fatma Benkhelifa, and Tibor Cinkler. 2021. "Analysis of Power Allocation for NOMA-Based D2D Communications Using GADIA" Information 12, no. 12: 510. https://doi.org/10.3390/info12120510