Abstract
In this work, we propose adaptable decision regions in the successive interference cancellation (SIC) decoder for the three-user uplink/downlink non-orthogonal multiple access (NOMA) scheme by exploiting the knowledge of the channel gains. We present scenarios in which the modified SIC decoder outperforms the traditional one and is able to replicate the performance achieved by a deep learning-based decoder. We present analytical symbol error rate (SER) expressions for the three users, compare them to simulation results, and discuss possible consequences of our analysis, such as the optimal power allocation. We also employ heatmaps to analyze the joint influence on the SER of some system parameters, such as signal-to-noise ratio and channel gains.
Highlights
Channel resource sharing techniques have been gaining importance due to the necessity of achieving higher spectral efficiency in the generations of wireless communications systems [1]
We consider in this work the scenario where arbitrary interference is present and a successive interference cancellation (SIC) modification is employed to handle decoding in high interference imperfect SIC cases by exploiting channel gain knowledge
We present an analytical expression for the symbol error rate (SER) of the first decoding step where the modified decision region is used and approximate formulas for the SER of the other users
Summary
Channel resource sharing techniques have been gaining importance due to the necessity of achieving higher spectral efficiency in the generations of wireless communications systems [1]. Power domain non-orthogonal multiple access (NOMA) is an important technique in accomplishing this task [2], which is frequently linked to 5G technologies [3] In this scheme, signals from multiple users with different power levels share the same channel resources, and the successive interference cancellation (SIC) is the usual decoding method, in which the decoding at each user is is performed sequentially according to the ordering of their power levels. We consider in this work the scenario where arbitrary interference is present and a SIC modification is employed to handle decoding in high interference imperfect SIC cases by exploiting channel gain knowledge.
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