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The research of power allocation algorithm with lower computational complexity for non-orthogonal multiple access

Ying Lin

Ying Lin

  • College of Electrical and Information Engineering, Lanzhou University of TechnologyLanzhou, China
  • School of Computer and Communication, Lanzhou University of TechnologyLanzhou, China
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Lin, Ying
, 
Suoping Li

Suoping Li

School of Science, Lanzhou University of TechnologyLanzhou, China
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Li, Suoping
, 
Kejun Jia

Kejun Jia

School of Computer and Communication, Lanzhou University of TechnologyLanzhou, China
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Jia, Kejun
 e 
Kathryn L. Kingsley

Kathryn L. Kingsley

Rutgers UniversityNew Brunswick, US
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Kingsley, Kathryn L.
  
08 apr 2021
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Pubblicato online: 08 apr 2021
Pagine: 79 - 88
Ricevuto: 29 nov 2020
Accettato: 31 gen 2021
DOI: https://doi.org/10.2478/amns.2021.1.00027
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© 2020 Ying Lin et al., published by Sciendo
This work is licensed under the Creative Commons Attribution 4.0 International License.

Fig. 1

The difference of power spectrum allocation between OFDMA and NOMA.
The difference of power spectrum allocation between OFDMA and NOMA.

Fig. 2

Illustration of tree topology power allocation.
Illustration of tree topology power allocation.

Fig. 3

System capacity of various power allocation algorithms under different numbers of users.
System capacity of various power allocation algorithms under different numbers of users.

Fig. 4

Computational complexity comparison of the proposed TTPA algorithm and other algorithms.
Computational complexity comparison of the proposed TTPA algorithm and other algorithms.

Algorithm of tree topology power allocation

1: Input: pre-processing SINRs of N users: set n=0, R = 0.2: Constructing and initialising the tree topology model; the number of multiplexed users in NOMA system is equal to the number of layers.3: Branch and node settings. Each branch represents the possible power allocation ratio for each user; each node corresponds to a possible power allocation ratio combination up to the nth layer.4: Intra-stage processing; for each node in the current stage, calculate the sum rate of each node in the current and previous stage. For each level, only keep the node with the largest sum rate. The other nodes are considered redundant and discarded to reduce computational complexity.5: Processing for the last stage. The branch number in level n equals to the number of nodes kept in stage N-1.6: For the last stage, βn equals to 1-∑i=1n-1βi 1 - \sum\nolimits_{i = 1}^{n - 1} {\beta _i} . The branch number in stage N equals to the number of nodes kept in stage N-1. The node which has the largest sum rate in each layer is considered to be the survival node.7: Trace back from the node which is determined in Steps 5 and 6, and then output the combination of power allocation ratio.
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Inglese
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