Vesa Turunen

Implementation of Cyclostationary Feature Detector for Cognitive Radios

Spectrum sensing is needed in cognitive radios to provide information about the surrounding radio spectrum. This enables cognitive radio system to communicate among existing radio systems without interfering them. This paper describes an FPGA implementation of a cyclostationary feature detector, which has an improved detection performance achieved by decimation of the cyclic spectrum. Decimation also provides a simple way to control detection time and, thus, allows trading the detection time to better probability of detection and vice versa. Measured detection performance is presented and detection of a 802.11g WLAN signal from air is demonstrated.

Correlation-Based Detection of OFDM Signals in the Angular Domain

Spectrum sensing is an essential part of future cognitive radios, as the spectrum sensor provides information about the utilization of the surrounding radio spectrum. Several approaches to implementing spectrum sensing have been proposed in the literature, one of them being the class of feature detectors. Cyclostationary feature detectors are, in general, considered to be superior in performance but suffer from high implementation complexity. Therefore, most studies still utilize energy detectors, which may not reach the performance requirements set for practical implementations. This paper presents angular domain feature detection algorithms that are based on cyclostationary properties. Angular domain signal processing is shown to simplify the implementation considerably while preserving comparable performance. Moreover, a new detection algorithm that leads to multiplier-free implementation and reduces the memory requirements, compared with any previous approaches, is proposed.

Survey and Analysis of Cyclostationary Signal Detector Implementations on FPGA

Detecting the presence of primary users and ability to find white spaces in the spectrum are the key enablers of the opportunistic communication. This paper analyzes the trade-offs in cyclostationary-based spectrum sensing algorithm implementations in terms of performance, hardware complexity, and power consumption. The evaluation of the algorithm implementations is performed on field-programmable gate arrays. The analysis presented will provide the designer understanding of dependency between algorithm complexity and power consumption, which is inherently limiting factor of implementation feasibility for cognitive mobile devices.

Spectrum estimator and cyclostattionary detector for cognitive radio

Spectrum sensing is one of the most challenging task in implementing future cognitive radios. The sensing unit should provide reliable information about the surrounding radio spectrum with small delay and low power consumption. This paper presents an implementation of a spectrum sensing unit capable of performing both cyclostationary feature detection and spectrum estimation for energy detection. A prototype is designed on a FPGA for measurement and demonstration, and synthesis for 65 nm CMOS process provides estimates for area and power consumption in an ASIC implementation.

On the implementation of autocorrelation-based feature detector

Emerging wireless systems demand more spectrum in order to provide high data rate services. It is known that most of the licensed frequency bands are underutilized because of the rigid spectrum allocation. Cognitive radios aim to relief the situation by identifying and exploiting the underutilized radio spectrum. A key task of the cognitive radio is spectrum sensing, which finds free spectrum and detects licensed spectrum user transmissions. This paper presents an FPGA implementation of an autocorrelation-based feature detector for OFDM-based primary user signals. The autocorrelation-based detection algorithm is optimized in order to achieve power and area efficient hardware realization. The algorithm is implemented in an FPGA evaluation environment, and the performance is verified with measurements.

FPGA implementation of autocorrelation-based feature detector for cognitive radio

Cognitive radio is an emerging technology in communication systems. Cognitive radios aim to relief the shortage of spectral resources by identifying and exploiting underutilized radio spectrum. A key task of the cognitive radio is spectrum sensing in order to find free spectrum and detect licensed spectrum user transmissions. In this paper, an FPGA implementation of a feature detector for OFDM-based primary user signals is presented. The detection algorithm, that was originally presented in , is modified in order to achieve power and area efficient hardware realization. The algorithm is implemented in an FPGA evaluation environment, and the performance is verified in simulation.

12-bit 2.4 GHz D/A upconverter

This paper describes the design and implementation of a upconverting D/A converter (DAC). Designed converter is capable of upconverting two 12-bit 60 MHz (in-phase and quadrature) signal bands around 2.4 GHz radio frequency. Upconversion is implemented by reorganizing switching scheme of a traditional current-steering D/A converter. Designed with 0.13 mum CMOS process, total area and estimated power consumption including DSP are 8.14 mm2 and 520 mW respectively.