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Concomitantly with the progress of wireless communications, cognitive radio has attracted attention as a solution for depleted frequency bands. Cognitive radio is suitable for wireless sensor networks because it reduces collisions and thereby achieves energy-efficient communication. To make cognitive radio practical, we propose a low-power multi-resolution spectrum sensing (MRSS) architecture that has flexibility in sensing frequency bands. The conventional MRSS scheme consumes much power and can be adapted only slightly to process scaling because it comprises analog circuits. In contrast, the proposed architecture carries out signal processing in a digital domain and can detect occupied frequency bands at multiple resolutions and with low power. Our digital MRSS module can be implemented in 180-nm and 65-nm CMOS processes using Verilog-HDL. We confirmed that the processes respectively dissipate 9.97 mW and 3.45 mW.

In this paper, we propose a reconfigurable baseband processor for a cognitive radio that has multi-resolution bandpass filters. By applying the distributed arithmetic algorithm to the reconfigurable baseband processor and rewriting SRAM data in it, a channel center frequency and bandwidth are reconfigurable. The filter bandwidth can be changed from 40 kHz to 240 kHz with a 10 kHz resolution on our prototype processor. The power is 13 mW at a supply voltage of 1.8 V in a 0.18-μm CMOS process.

This paper presents an ultra-low-power single-chip sensor-node VLSI for wireless-sensor-network applications. A communication centric design approach has been introduced to reduce the power consumption of the RF circuits and the entire sensor network system, through a vertical cooperative design among circuits, architecture, and communication protocols. The sensor-node LSI features a synchronous media access control (MAC) protocol and integrates a transceiver, i8051 microcontroller, and dedicated MAC processor. The test chip occupies 3 × 3 mm 2 in a 180-nm CMOS process, including 1.38 M transistors. It dissipates 58.0 μW under a network environment.