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EN
The future Internet of Things (IoT) era is anticipated to support computation-intensive and time-critical applications using edge computing for mobile (MEC), which is regarded as promising technique. However, the transmitting uplink performance will be highly impacted by the hostile wireless channel, the low bandwidth, and the low transmission power of IoT devices. Using edge computing for mobile (MEC) to offload tasks becomes a crucial technology to reduce service latency for computation-intensive applications and reduce the computational workloads of mobile devices. Under the restrictions of computation latency and cloud computing capacity, our goal is to reduce the overall energy consumption of all users, including transmission energy and local computation energy. In this article, the Deep Q Network Algorithm (DQNA) to deal with the data rates with respect to the user base in different time slots of 5G NOMA network. The DQNA is optimized by considering more number of cell structures like 2, 4, 6 and 8. Therefore, the DQNA provides the optimal distribution of power among all 3 users in the 5G network, which gives the increased data rates. The existing various power distribution algorithms like frequent pattern (FP), weighted least squares mean error weighted least squares mean error (WLSME), and Random Power and Maximal Power allocation are used to justify the proposed DQNA technique. The proposed technique which gives 81.6% more the data rates when increased the cell structure to 8. Thus 25% more in comparison to other algorithms like FP, WLSME Random Power and Maximal Power allocation.
EN
Non-Orthogonal Multiple Access (NOMA) in the fifth generation (5G) system is one of the optimistic technologies for wireless radio access networks. Compared to orthogonal multiple accesses (OMA) reduce the spectral efficiency; NOMA provides the best solution by increasing the data rates. This study evaluates NOMA with a downlink in the automatic deployment of multiusers. The outage performance and ergotic sum-rate gain give the NOMA better performance can be concluded at the final results. NOMA provides the Quality of Service (QoS) to the multi-users by considering the power allocation and data rate factors. Here is considered the outage probability will be 1 when it identifies the different user and allocates the data rate and power.
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