| Title |
Power Optimization in a Multicell D2D Communication for Smart City in an mm-Wave Cellular Network: An mIoT Perspective |
| ID_Doc |
42538 |
| Authors |
Sarma, SS; Hazra, R; Goswami, P |
| Title |
Power Optimization in a Multicell D2D Communication for Smart City in an mm-Wave Cellular Network: An mIoT Perspective |
| Year |
2023 |
| Published |
Ieee Internet Of Things Journal, 10, 21 |
| DOI |
10.1109/JIOT.2023.3262577 |
| Abstract |
Device-to-device (D2D) communication ushers the realization of massive Internet of Things (mIoT) network for smart cities through long term evolution-advanced (LTE-A). In a multicell mm-Wave environment, acute interference from adjacent cells degrades the signal quality. Thus, our work focuses on the minimization of interference from the neighboring cells through optimal resource allocation and power optimization. Rate-splitting multiple access (RSMA) technique is employed where the message to be transmitted is divided into two parts. Two modes for resource allocation are formulated which aims to maximize the throughput under certain interference constraints. The radius of coverage expression is derived for switching of modes to take place. Successive interference cancelation (SIC) is introduced as a power constraint which enhances the overall performance of the network. Subsequently, Lagrange's dual-optimization method is utilized for optimizing the D2D transmit power and also lowering the computational complexity of the overall network. Simulation results depict the overall performance efficiency in terms of transmission rate and signal strength. The results show that with the increase in difference of transmit power allocated to the common and private message, overall transmission rate also increases significantly. Finally, comparison with existing scheme validates the efficiency of the proposed work. |
| Author Keywords |
5G mm-Wave network; device-to-device (D2D) communication; Lagrangian dual-optimization technique; power optimization; rate-splitting multiple access (RSMA); resource allocation |
| Index Keywords |
Index Keywords |
| Document Type |
Other |
| Open Access |
Open Access |
| Source |
Science Citation Index Expanded (SCI-EXPANDED) |
| EID |
WOS:001098109800025 |
| WoS Category |
Computer Science, Information Systems; Engineering, Electrical & Electronic; Telecommunications |
| Research Area |
Computer Science; Engineering; Telecommunications |
| PDF |
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