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Maximizing Connection Density in NB-IoT Networks with NOMA

Abstract : We address the issue of maximizing the number of connected devices in a Narrowband Internet of Things (NB-IoT) network using non-orthogonal multiple access (NOMA). The scheduling assignment is done on a per-transmit time interval (TTI) basis and focuses on efficient device clustering. We formulate the problem as a combinatorial optimization problem and solve it under interference, rate and sub-carrier availability constraints. We first present the bottom-up power filling algorithm (BU), which solves the problem given that each device can only be allocated contiguous sub-carriers. Then, we propose the item clustering heuristic (IC) which tackles the more general problem of non-contiguous allocation. The novelty of our optimization framework is twofold. First, it allows any number of devices to be multiplexed per sub-carrier, which is based on the successive interference cancellation (SIC) capabilities of the network. Secondly, whereas most existing works only consider contiguous sub-carrier allocation, we also study the performance of allocating non-contiguous sub-carriers to each device. We show through extensive simulations that non-contiguous allocation through IC scheme can outperform BU and other existing contiguous allocation methods.
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Submitted on : Tuesday, May 12, 2020 - 4:34:04 PM
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  • HAL Id : hal-02571150, version 1

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Shashwat Mishra, Lou Salaun, Chung Shue Chen. Maximizing Connection Density in NB-IoT Networks with NOMA. IEEE VTC 2020-Spring, May 2020, Antwerp, Belgium. ⟨hal-02571150⟩

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