Andre B.J. Kokkeler

An Efficient FFT For OFDM Based Cognitive Radio On A Reconfigurable Architecture

Cognitive radio is a promising technology to utilize non-used parts of the spectrum that actually are assigned to licensed services. An adaptive OFDM based cognitive radio system has the capacity to nullify individual carriers to avoid interference to the licensed user. Therefore, there could be a considerably large number of zero-valued inputs/outputs for the IFFT/FFT in the OFDM transceiver. Due to the wasted operations on zero values, the standard FFT is no longer efficient. Based on this observation, we propose to use a computationally efficient IFFT/FFT as an option for OFDM based cognitive radio. Mapping this algorithm onto a reconfigurable architecture is discussed.

Lowering the SNR Wall for Energy Detection Using Cross-Correlation

Spectrum sensing is a key enabler of cognitive radio but generally suffers from what is called a signal-to-noise ratio (SNR) wall, i.e., a minimum SNR below which it is impossible to reliably detect a signal. For energy detection, which has the advantage of not requiring knowledge of the signal, the SNR wall is caused by uncertainty in the noise level. Cross-correlation has been suggested as a possible means to obtain higher sensitivity but has received little attention in the context of noise uncertainty. The idea of cross-correlation is to have two receive paths, where each path independently processes the signal before they are combined, such that the noise added to the input signal at the individual paths is largely uncorrelated. In this paper, we mathematically quantify the SNR wall for cross-correlation, showing that it linearly scales with the amount of noise correlation. This lower noise correlation results in higher sensitivity, which is significantly better than that for autocorrelation. Equations that can be used to estimate the benefit over autocorrelation and the measurement time for a required probability of detection and false alarm are derived.

A Reconfigurable Radio Architecture for Cognitive Radio in Emergency Networks

Cognitive radio has been proposed as a promising technology to solve todays spectrum scarcity problem. Cognitive radio is able to sense the spectrum to find the free spectrum, which can be optimally used by cognitive radio without causing interference to the licensed user. In the scope of the adaptive ad-hoc freeband (AAF) project, an emergency network built on top of cognitive radio is proposed. New functional requirements and system specifications for cognitive radio have to be supported by a reconfigurable architecture. In this paper, we propose a heterogenous reconfigurable system-on-chip (SoC) architecture to enable the evolution from the traditional software defined radio to cognitive radio

An efficient multi-resolution spectrum sensing method for cognitive radio

This paper presents a novel energy based multi-resolution spectrum sensing technique. By applying an efficient flexible FFT, the proposed method can focus on a small part of the interested bands with finer resolutions at low computational cost. The hardware implementation of the algorithm has been considered. An experiment on a reconfigurable platform shows that the algorithm is not only computationally efficient but can also easy to be reconfigured easily and fast.

The Chameleon architecture for streaming DSP applications

We focus on architectures for streaming DSP applications such as wireless baseband processing and image processing. We aim at a single generic architecture that is capable of dealing with different DSP applications. This architecture has to be energy efficient and fault tolerant. We introduce a heterogeneous tiled architecture and present the details of a domain-specific reconfigurable tile processor called Montium. This reconfigurable processor has a small footprint (1.8 mm2 in a 130 nm process), is power efficient and exploits the locality of reference principle. Reconfiguring the device is very fast, for example, loading the coefficients for a 200 tap FIR filter is done within 80 clock cycles. The tiles on the tiled architecture are connected to a Network-on-Chip (NoC) via a network interface (NI). Two NoCs have been developed: a packet-switched and a circuit-switched version. Both provide two types of services: guaranteed throughput (GT) and best effort (BE). For both NoCs estimates of power consumption are presented. The NI synchronizes data transfers, configures and starts/stops the tile processor. For dynamically mapping applications onto the tiled architecture, we introduce a run-time mapping tool.

A 50Mhz-To-1.5Ghz Cross-Correlation CMOS Spectrum Analyzer for Cognitive Radio with 89dB SFDR in 1Mhz RBW

Spectrum sensing for cognitive radio requires a high linearity to handle strong signals, and at the same time a low noise figure (NF) to enable detection of much weaker signals. Often there is a trade-off between linearity and noise: improving one of them degrades performance of the other. Cross-correlation can break this trade-off by reducing noise at the cost of measurement time. An existing RF front-end in CMOS-technology with IIP3=+11dBm and NF<6.5dB is duplicated and attenuators are put in front to increase linearity (IIP3=+24dBm). The attenuation degrades NF, but by using cross-correlation of the outputs of the two front-ends, the NF is reduced to below 4dB. In total this results in a spurious-free dynamic range (SFDR) of 89dB in 1MHz resolution bandwidth (RBW).

Spurious-Free Dynamic Range of a Uniform Quantizer

Quantization plays an important role in many systems where analog-to-digital conversion and/or digital-to-analog conversion take place. If the quantization error is correlated with the input signal, then the spectrum of the quantization error will contain spurious peaks. Although analytical formulas describing this effect exist, numerical evaluation can take much effort. This brief provides approximations for the spurious-free dynamic range (SFDR) of a uniform quantizer with a single sinusoidal input, with and without additive Gaussian noise. It is shown that the SFDR increases by approximately 8 dB/bit, in case there is no noise. Generalizing this result to multitone inputs results in an additional 2 dB/bit per additional tone. Additive Gaussian noise decorrelates the sinusoid(s) and the quantization error, which results in a dramatic increase in SFDR.

CRISP: Cutting Edge Reconfigurable ICs for Stream Processing

The Cutting edge Reconfigurable ICs for Stream Processing (CRISP) project aims to create a highly scalable and dependable reconfigurable system concept for a wide range of tomorrow’s streaming DSP applications. Within CRISP, a network-on-chip based many-core stream processor with dependability infrastructure and run-time resource management is devised, implemented, and manufactured to demonstrate a coarse-grained core-level reconfigurable system with scalable computing power, flexibility, and dependability. This chapter introduces CRISP, presents the concepts, and outlines the preliminary results of a running project.

A CMOS-Compatible Spectrum Analyzer for Cognitive Radio Exploiting Crosscorrelation to Improve Linearity and Noise Performance

A spectrum analyzer requires a high linearity to handle strong signals, and at the same time a low NF to enable detection of much weaker signals. This is not only important for lab equipment, but also for the spectrum sensing part of cognitive radio, where low cost and integration is at a premium. Often there is a trade-off between linearity and noise: improving one degrades the other. Crosscorrelation can break this trade-off by reducing noise at the expense of measurement time. An existing RF frontend in CMOS-technology with IIP3 = +11 dBm and NF = 5.5 dB is duplicated and attenuators are put in front to increase linearity to IIP3 = +24 dBm. The attenuation degrades NF, but by using crosscorrelation of the outputs of the two frontends, the effective NF is reduced to around 5 dB. In total, this results in a spurious-free dynamic range of 88 dB in 1 MHz resolution bandwidth.

An oversampled filter bank multicarrier system for Cognitive Radio

Due to small sideband power leakage, filter bank multicarrier techniques are considered as interesting alternatives to traditional OFDMs for spectrum pooling cognitive radio. In this paper, we propose an oversampled filter bank multicarrier system for cognitive radio. The increased spacing between adjacent subcarriers in the oversampled filter bank multicarrier system largely reduce the intercarrier interference, the key limitation of the OFDM based cognitive radio. The proposed multicarrier system is compared with OFDM for BER performance and sideband power rejection. Design tradeoffs of the major parameters of the oversampled filter bank will be discussed. We also suggest a fast implementation of the proposed filter bank modulation based on generalized DFT filter bank model, followed by a computational complexity analysis.