BayGo
This article deals with the problem of distributed machine learning, in which agents update their models based on their local datasets, and […]
On the SIR Meta Distribution in Massive MTC Networks with Scheduling and Data Aggregation
Data aggregation is an efficient approach to handle the congestion introduced by a massive number of machine type devices (MTDs). The aggregators […]
Hybrid resource scheduling for aggregation in massive machine-type communication networks
Data aggregation is a promising approach to enable massive machine-type communication (mMTC). Here, we first characterize the aggregation phase where a massive […]
Aggregation and Resource Scheduling in Machine-Type Communication Networks
Data aggregation is a promising approach to enable massive machine-type communication. This paper focuses on the aggregation phase where a massive number […]