On the stability and throughput of compressive random access in MTC
Jinho Choi
Abstract
Jinho Choi
Abstract
Compressive random access has been considered for machine-type communications (MTC) as it has a potential to support massive connectivity by exploiting the sparsity of device activity. However, its performance limitations are not well studied yet compared with other well-known candidates for MTC, e.g., multichannel ALOHA. In this paper, we investigate the stability of compressive random access with a controlled access probability strategy and derive the maximum stable throughput to see performance limitations. From the analysis results, we can show that the maximum stable throughput of compressive random access is higher than that of multichannel ALOHA by a factor of 2. As a result, we can claim that compressive random access can support more devices than multichannel ALOHA in MTC.
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Compressive random access has been considered for machine-type communications (MTC) as it has a potential to support massive connectivity by exploiting the sparsity of device activity. However, its performance limitations are not well studied yet compared with other well-known candidates for MTC, e.g., multichannel ALOHA. In this paper, we investigate the stability of compressive random access with a controlled access probability strategy and derive the maximum stable throughput to see performance limitations. From the analysis results, we can show that the maximum stable throughput of compressive random access is higher than that of multichannel ALOHA by a factor of 2. As a result, we can claim that compressive random access can support more devices than multichannel ALOHA in MTC.
Key concepts: Aloha, Random access, Throughput, Computer science, Compressed sensing, Stability (learning theory), Computer network, Algorithm