Concurrent Transmission and Multiuser Detection of LoRa Signals
The Khai Nguyen, Ha H. Nguyen, Ebrahim Bedeer

TL;DR
This paper proposes a novel multiuser detection model for LoRa networks that enables simultaneous transmissions from multiple devices, significantly increasing network capacity with manageable power control and detection complexity.
Contribution
It introduces a new detection algorithm and power optimization method to enhance LoRa network scalability with concurrent device transmissions.
Findings
Doubling or tripling uplink capacity with 2 or 3 concurrent EDs.
Tradeoff between increased capacity and additional transmit power.
Effective power control via successive convex approximation.
Abstract
This paper investigates a new model to improve the scalability of low-power long-range (LoRa) networks by allowing multiple end devices (EDs) to simultaneously communicate with multiple multi-antenna gateways on the same frequency band and using the same spreading factor. The maximum likelihood (ML) decision rule is first derived for non-coherent detection of information bits transmitted by multiple devices. To overcome the high complexity of the ML detection, we propose a sub-optimal two-stage detection algorithm to balance the computational complexity and error performance. In the first stage, we identify transmit chirps (without knowing which EDs transmit them). In the second stage, we determine the EDs that transmit the specific chirps identified from the first stage. To improve the detection performance in the second stage, we also optimize the transmit powers of EDs to minimize…
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Taxonomy
TopicsAdvanced MIMO Systems Optimization · Energy Harvesting in Wireless Networks · IoT Networks and Protocols
