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D2D communication as a multi-agents system, and power control is achieved by maximizing system capacity while maintaining the requirement of quality of service(QoS) from cellular users.

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nikhil-feb/Q-Learning-Based-Power-Control-Algorithm-for-D2D-Communication

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Q-Learning-Based-Power-Control-Algorithm-for-D2D-Communication

Device-to-Device (D2D) communication is a promising technology of 5G cellular networks.

D2D communication aims at establishing a direct communication link between the user equipments, located in the close proximity of each other, instead of traversing through the core network.

D2D communications can be in-band and out-band. Furthermore, it can be underlay and overlay in in-band whereas controlled and autonomous in out-band.

Need of power control :

In in-band underlay D2D communication networks, D2D devices use the frequency band being used by the cellular devices without any pre-allocation.

Consider a system where we have some D2D users and cellular users co-existing in the same cell and employing same frequency band.

For the users sharing same resource blocks, D2D users will suffer from the interference from the cellular users and other D2D users.

Cellular users will also suffer from the interference from the D2D users.

Cellular users have a constraint on SINR for maintaining QoS.

This in-turn imposes a constraint on the power levels of the D2D users.

Problem statement :

We need to determine the optimum power of the D2D users, sharing the same resource blocks with the cellular users, such that the QoS constraint of cellular users can be met successfully.

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D2D communication as a multi-agents system, and power control is achieved by maximizing system capacity while maintaining the requirement of quality of service(QoS) from cellular users.

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