Abstract

One of the key tasks in cognitive radio and communications intelligence is to detect active bands in the radio-frequency (RF) spectrum. In order to perform spectral activity detection in wideband RF signals, expensive and energy-inefficient high-rate analog-to-digital converters (ADCs) in combination with sophisticated digital detection circuitry are typically used. In many practical situations, however, the RF spectrum is sparsely populated, i.e., only a few frequency bands are active at a time. This property enables the design of so-called analog-to-information (A2I) converters, which are capable of acquiring and directly extracting the spectral activity information at low cost and low power by means of compressive sensing (CS). In this paper, we present the first very-large-scale integration (VLSI) design of a monolithic wideband CS-based A2I converter that includes a signal acquisition stage capable of acquiring RF signals having large bandwidths and a high-throughput spectral activity detection unit. Low-cost wideband signal acquisition is obtained via CS-based randomized temporal subsampling in combination with a 4-bit flash ADC. High-throughput spectrum activity detection from the coarsely quantized and compressive measurements is achieved by means of a massively-parallel VLSI design of a novel accelerated sparse spectrum dequantization (ASSD) algorithm. The resulting monolithic A2I converter is designed in 28 nm CMOS, acquires RF signals up to 6 GS/s, and the on-chip ASSD unit detects the active RF bands at a rate 30 × below real-time.

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