Delay Minimization for Massive Internet of Things With Non-Orthogonal Multiple Access

2019 ◽  
Vol 13 (3) ◽  
pp. 553-566 ◽  
Author(s):  
Daosen Zhai ◽  
Ruonan Zhang ◽  
Lin Cai ◽  
F. Richard Yu
2021 ◽  
Author(s):  
Huseyin Haci ◽  
Joydev Ghosh

<div>Non-orthogonal multiple access (NOMA) is shown to be the optimal channel access method and a strong candidate to be employed at the fifth generation (5G) and beyond networks. This paper studies direct transmission (DT) and cooperative transmission (CT) modes of operations in NOMA communications and proposes an investigation on evolving a cooperative transmission NOMA (C-NOMA) into a Hybrid transmission NOMA (H-NOMA) that can be used for design and deployment of relay based wireless networks, such as networks for Internet of Things (IoT) applications.</div>


Sensors ◽  
2019 ◽  
Vol 19 (4) ◽  
pp. 912
Author(s):  
Minjoong Rim ◽  
Chung Kang

One of the key requirements for next generation wireless or cellular communication systems is to efficiently support a large number of connections for Internet of Things (IoT) applications, and uplink non-orthogonal multiple access (NOMA) schemes can be used for this purpose. In uplink NOMA systems, pilot symbols, as well as data symbols can be superimposed onto shared resources. The error rate performance can be severely degraded due to channel estimation errors, especially when the number of superimposed packets is large. In this paper, we discuss uplink NOMA schemes with channel estimation errors, assuming that quadrature phase shift keying (QPSK) modulation is used. When pilot signals are superimposed onto the shared resources and a large number of devices perform random accesses concurrently to a single resource of the base station, the channels might not be accurately estimated even in high SNR environments. In this paper, we propose an uplink NOMA scheme, which can alleviate the performance degradation due to channel estimation errors.


IEEE Access ◽  
2016 ◽  
Vol 4 ◽  
pp. 4583-4589 ◽  
Author(s):  
Su Hu ◽  
Huiting Guo ◽  
Chuanxue Jin ◽  
Yixuan Huang ◽  
Bin Yu ◽  
...  

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