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Quantization plays a critical role in digital signal processing systems,allowing the representation of continuous amplitude signals with a finitenumber of bits. However, accurately representing signals requires a largenumber of quantization bits, which causes severe cost, power consumption, andmemory burden. A promising way to address this issue is task-basedquantization. By exploiting the task information for the overall system design,task-based quantization can achieve satisfying performance with lowquantization costs. In this work, we apply task-based quantization tomulti-user signal recovery and present a hardware prototype implementation. Theprototype consists of a tailored configurable combining board, and asoftware-based processing and demonstration system. Through experiments, weverify that with proper design, the task-based quantization achieves areduction of 25 fold in memory by reducing from 16 receivers with 16 bits eachto 2 receivers with 5 bits each, without compromising signal recoveryperformance.

Hardware Implementation of Task-based Quantization in Multi-user Signal Recovery