Device-to-Device (D2D) communication refers to a technology that enables devices to communicate directly with each other, without sending data to the base station and the core network. This technology has the potential to improve system performance, enhance the user experience, increase spectral efficiency, reduce the terminal transmitting power, reduce the burden of the cellular network, and expand cellular applications.
In D2D communication UEs are enabled to select among different Transmission Modes (TM)s which are defined based on the frequency resource sharing. Dedicated mode where the D2D communication is direct and data is transmitted through the D2D link by the orthogonal frequency resources to the cellular users so there is not any interference. Reuse mode where data is transmitted through the D2D link by reusing the same frequency resources that are considered for a cellular user or another D2D link so reused mode causes interference at receivers however, the system spectrum efficiency and user access rate may be increased. Cellular mode where the D2D communication is relayed via eNB and it is treated as cellular users.
In this work, we aim to reach the optimal mode selection policy, and we use the Markov Decision Process (MDP) method with the objective of maximizing the total expected reward per connection. We present and analyse optimal mode selection policy for several scenarios with different rewards and cost for cellular, dedicated and reused mode.
In our study of mode selection issues in D2D enabled network we propose an algorithm for the case when the cellular UE moves in the network. We use QoS parameters, mobility parameters and Analytic Hierarchy Process (AHP) method to define new mobility based mode selection algorithm. To evaluate our proposed algorithm, we considered SNR and delay.
| Date | 1 Nov 2018 |
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| Original language | American English |
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| Awarding Institution | - École de technologie supérieure
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| Supervisor | Zbigniew Dziong (Supervisor) |
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Habibimarekani, M. (Author),
Dziong (Supervisor),
1 Nov 2018Student thesis: Master's thesis › Master in Engineering: Electrical Engineering