Steffen Riess

A Spectrum Sensing Network for Cognitive PMSE Systems

Abstract This article is about a Spectrum Sensing Network (SSN) which generates an accurate radio environment map (e.g. power over frequency, time, and location) from a given application area. It is intended to be used in combination with cognitive Program Making and Special Events (PMSE) devices (e.g. wireless microphones) to improve their operation reliability. The SSN consists of a distributed network of multiple scanning radio receivers and a central data management and storage unit. The parts of the SSN are presented in detail and the advantages and use cases of such a sensing network structure will be outlined.

A low cost ultra-wide-band inverted F-antenna for cognitive PMSE systems

In this paper, a very cheap ultra-wideband antenna has been proposed. The measured return loss is less than -10 dB within a frequency range from 463 to 1060 MHz and, despite a non-constant εr due to substrate material tolerances, the measurements match the simulation results up to a frequency of 900 MHz. It can also be shown, that the divergences of simulated and measured return loss for frequencies higher than 900 MHz are due to inaccuracy of the production process. The antenna is very easy to produce and besides very cheap.

Model-based implementation for the calculation of Power Spectral Density in an FPGA system

Cognitive Radio (CR) systems equipped with a spectrum sensing unit are able to access the radio frequency spectrum in a dynamic manner. This paper presents a model-based design approach and implementation for the calculation of the Power Spectral Density (PSD) of the received signal in a spectrum scanner. Design parameters based on the requirements of the complete CR system as well as the signal processing steps for the PSD calculation are described. The signal processing comprises the implementation of a control unit, selectable window functions, the Fast Fourier Transformation, the calculation of the magnitude, selectable number of averages for the calculation of peak and mean power values as well as the logarithmic representation of the spectrum. The presented processing block is integrated as part of an embedded system in an FPGA. The simulation and measurement results demonstrate and proof the functionality of the developed block with the shown design flow.

Concept of an UHF band receiver for spectrum sensing applications

Spectrum sensing is a major part for the implementation of Cognitive Radio (CR) systems in order to enable dynamic access to the radio frequency spectrum. This paper describes a concept for a scanning receiver in the UHF band from 470 - 870 MHz. Characteristics and design considerations of an Analog and Digital Front-End are given as well as the implementation of a Baseband Processor. This is the central module of the whole receiver and the interface to a higher-level controlling unit connected through a 100 Mbit/s Ethernet link. The control interface for the receiver is similar to a spectrum analyzer and therefore easy integrable in an already existing system. Special attention in the digital part is paid to an IF subsampling approach and the clock generation circuit for the ADC. For the sake of completeness the interface to a configurable antenna and some details to the realization of the power supply are also described. This concept has been implemented in hardware in order to enable investigations for the task of spectrum sensing. Our scanning receiver is part of a complex CR system for Professional Wireless Microphone Systems (PWMS) which should be able to provide a dynamic frequency allocation of the connected radio links.

Noise floor dependent data fusion for reliable REM generation with a spectrum sensing grid

For several years the cognitive radio (CR) technology is under research as promising solution supporting the efficient utilization of the scarce radio frequency spectrum. The cognitive cycle enables the adaptation of operating parameters according to observations made from the environment. A radio environment map (REM) which contains data from spectrum sensing devices was identified to be an adequate tool to realize CR systems. In this contribution the challenges in generating a REM from sensor nodes with limited dynamic range is pointed out. Afterward, the noise floor dependent data fusion (NDDF) algorithm is proposed. It is able to generate a reliable REM in a fusion center of a sensing grid. The algorithm merges spectrum measurements from collocated sensor nodes to reduce the amount of data whilst preserving all advantages gained from macro diversity by taking into account the noise floor of each sensor. The algorithm has been verified with measurements in the laboratory and a measurement study at the fairground of Berlin shows the applicability of the NDDF algorithm.

Signal detection and cooperative sensing with sensor nodes with limited dynamic

The paper investigates the performance of the energy detector in fading environments under the constraint, that each sensor has only a limited dynamic range. First, the effects which limit the dynamic of a sensor node are discussed before the influence on the energy detector is analyzed. Simulations are presented how cooperative spectrum sensing affects the detection probability and it is shown that a sensing network with limited dynamic can gain much more from cooperation compared to a sensor network with ideal sensor nodes.

Enhancing open loop beamsteering performance for the uplink of UMTS/HSPA+ under Discontinuous Transmission

So called open loop transmit diversity algorithms for the uplink of UMTS use the power control commands as feedback to iteratively determine the antenna weights. The algorithms presented in literature so far are designed for continuous transmission. The UMTS standard, however, also allows discontinuous uplink transmission (DTX), which impairs the performance of these algorithms. This paper studies these impairments and proposes a method to design transmit diversity algorithms with improved performance in a DTX scenario. With such improved algorithms, the transmit power gain is 1.4 dB in DTX, which is an improvement of 0.7 dB over conventional non-DTX diversity algorithms.