Abstract
This paper performs a comprehensive survey on transmission schemes for the large‐scale Internet of things (IoT) networks with nonorthogonal multiple access (NOMA). By solving the interference among users, NOMA can significantly improve the frequency reuse efficiency and support multiple users to use the same frequency resources. It is considered to be one of the most effective technologies for the next‐generation wireless communication. However, there are still many challenges on the transmission schemes for the large‐scale NOMA system, including the short‐data packet transmission, active user detection, channel estimation, and data detection. In order to meet these challenges, this paper first reviews the short‐packet transmission in the large‐scale NOMA systems and then reviews the active user detection and channel estimation technologies of the considered systems.
Highlights
The application of Internet of things (IoT) has promoted a significant increase in data traffic of wireless networks [1,2,3]
This paper studies the nonorthogonal transmission and signal detection of large-scale IoT from the following three aspects: (1) from the perspective of short-data packet transmission, we design a reliable nonorthogonal transmission scheme for the cellular IoT uplink and downlink and analyze the system error performance and its influencing factors, (2) we study the characteristics of fast fading of nonzero elements of sparse signals and design efficient and reliable active user detection algorithms to reduce the false alarm rate of IoT user activity detection, thereby improving the utilization of spectrum resources, and (3) from the structural characteristics of double signal sparsity, we use Bayesian inference and optimization theory to design estimation algorithms for the user activity, channel jointly, and data, reducing the pilot overhead for reliable information transmission
We performed a comprehensive survey on the transmission schemes for large-scale IoT with nonorthogonal multiple access (NOMA), which could support multiple users to use the same frequency resources as long as the interference among users could be addressed
Summary
The application of Internet of things (IoT) has promoted a significant increase in data traffic of wireless networks [1,2,3]. This paper studies the nonorthogonal transmission and signal detection of large-scale IoT from the following three aspects: (1) from the perspective of short-data packet transmission, we design a reliable nonorthogonal transmission scheme for the cellular IoT uplink and downlink and analyze the system error performance and its influencing factors, (2) we study the characteristics of fast fading of nonzero elements of sparse signals and design efficient and reliable active user detection algorithms to reduce the false alarm rate of IoT user activity detection, thereby improving the utilization of spectrum resources, and (3) from the structural characteristics of double signal sparsity, we use Bayesian inference and optimization theory to design estimation algorithms for the user activity, channel jointly, and data, reducing the pilot overhead for reliable information transmission. For the large-scale NOMA, a series of topics such as the design of nonorthogonal transmission scheme with a short data packet, reliable detection algorithm with low complexity, and the reduction of system signaling overhead and transmission latency are very challenging. The problems mentioned above have essential theory and application value for the planning and deploying the large-scale multiple access technology in IoT networks
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