A Monitoring Network for Spectrum Governance

Dynamic Spectrum Access (DSA) is an exciting new technology, which has introduced a paradigm shift in spectrum access. As a result it also changes the role of the regulator. On one hand the scarce radio spectrum should be used in an optimal way, so that society is best served. On the other hand interference between users and between networks should be avoided. For that reason rules have to be defined for spectrum use. This topic is called spectrum governance. For evaluation and to check whether devices obey the rules, a monitoring system is needed. In this paper, we propose to use a fleet of mobile monitoring vehicles for this purpose.\u

Channel selection requirements for Bluetooth receivers using a simple demodulation algorithm

In our Software Defined Radio (SDR) project we combine two different types of standards, Bluetooth and HiperLAN/2, on one common hardware platform. SDR system research aims at the design, implementation and deployment of flexible radio systems that are reprogrammable and re-configurable by software. Goal of our project is to generate knowledge about designing the front end of an SDR system (from the antenna signal to the channel bit stream) where especially an approach from both analog and digital perspective is essential. This paper discusses the channel selection requirements for the Bluetooth standard. The standard specifications specify only the power level of the interferers, the power level of the wanted signal and the maximum allowed Bit Error Rate (BER). In order to build a radio front-end, one has to know the required (channel) suppression of these interferers. From [1] it is known that the required SNR for a Bluetooth demodulator is 21 dB, but by which value should interferers be suppressed? This paper will validate if the SNR value needs to be used for the suppression of adjacent channels. In order to answer this question a simulation model of a Bluetooth radio front-end is built

Spectral Weighting Functions for Single-symbol Phase-noise Specifications in OFDM Systems

For the specification of phase-noise requirements for the front-end of a HiperLAN/2 system we investigated available literature on the subject. Literature differed in several aspects. One aspect is in the type of phase-noise used (Wiener phase-noise or small-angle phase noise). A Wiener phase-noise based analysis leads to contradictions with the type of analysis normally used in the solid state oscillator literature. However, a phase-noise spectrum with a Wiener phase-noise shape can be used provided that the small-angle approximation is satisfied. An other aspect is whether a Fourier Series or DFT based approach is used. The approaches use weighting functions to relate phase-noise power spectral densities to phase-noise power. The two types of analysis are presented in a unified fashion that allows easy comparison of the weighting functions involved. It can be shown that for practical purposes results are identical. Finally phase-noise specifications for the Hiper-LAN/2 case are presented

A Real-Time GPP Software-Defined Radio Testbed for the Physical Layer of Wireless Standards

We present our contribution to the general-purpose-processor-(GPP)-based radio. We describe a baseband software-defined radio testbed for the physical layer of wireless LAN standards. All physical layer functions have been successfully mapped on a Pentium 4 processor that performs these functions in real time. The testbed consists of a transmitter PC with a DAC board and a receiver PC with an ADC board. In our project, we have implemented two different types of standards on this testbed, a continuous-phase-modulation-based standard, Bluetooth, and an OFDM-based standard, HiperLAN/2. However, our testbed can easily be extended to other standards, because the only limitation in our testbed is the maximal channel bandwidth of 20 MHz and of course the processing capabilities of the used PC. The transmitter functions require at most 714 M cycles per second and the receiver functions need 1225 M cycles per second on a Pentium 4 processor. In addition, baseband experiments have been carried out successfully

The Front end of Software-Defined Radio: Possibilities and Challenges

The use of mobile telephony has shown a spectacular\ud growth in the last 10 years. A side effect of this rapid\ud growth is an excess of mobile system standards. Therefore,\ud the Software-Defined-Radio (SDR) concept is emerging as\ud a potential pragmatic solution: it aims to build flexible radio\ud systems, which are multi-service, multi-standard, multiband,\ud re-configurable and re-programmable, by software.\ud First, this paper presents a global overview of SDR.\ud Furthermore, it discusses several front-end architectures of\ud SDR. The goal of this project is to generate knowledge about\ud designing part of the functionality of SDR, implemented by\ud rapid prototyping strategies. The focus is on the front end\ud of SDR. The technological roadmap is taken into account to\ud evaluate several architectures

Undetected error probability for data services in a terrestrial DAB single frequency network

DAB (Digital Audio Broadcasting) is the European successor of FM radio. Besides audio services, other services such as traffic information can be provided.\ud An important parameter for data services is the probability of non-recognized or undetected errors in the system. To derive this probability, we propose a bound for the undetected error probability in CRC codes. In addition, results from measurements of a Single Frequency Network (SFN) in Amsterdam were used, where the University of Twente conducted a DAB field trial. The proposed error bound is compared with other error bounds from literature and the results are validated by simulations. Although the proposed bound is less tight than existing bounds, it requires no additional information about the CRC code such\ud as the weight distribution. Moreover, the DAB standard has been extended last year by an Enhanced Packet Mode (EPM) which provides extra protection for data services. An undetected error probability for this mode is also derived. In a realistic user scenario of 10 million users, a 8 kbit/s EPM sub channel can be considered as a system without any undetected errors (Pud = 6 · 10−40). On\ud the other hand, in a normal data sub channel, only 110 packets with undetected errors are received on average each year in the whole system (Pud = 5 · 10−13)

Opportunistic Error Correction for WLAN Applications

The current error correction layer of IEEE 802.11a WLAN is designed\ud for worst case scenarios, which often do not apply. In this paper,\ud we propose a new opportunistic error correction layer based on\ud Fountain codes and a resolution adaptive ADC. The key part in the\ud new proposed system is that only packets are processed by the\ud receiver chain which have encountered ``good'' channel conditions.\ud Others are discarded. With this new approach, around $\frac{2}{3}$\ud of the energy consumption can be saved compared with the\ud conventional IEEE 802.11a WLAN system under the same channel\ud conditions and throughput

An Opportunistic Error Correction Layer for OFDM Systems

In this paper, we propose a novel cross layer scheme to lower power\ud consumption of ADCs in OFDM systems, which is based on resolution\ud adaptive ADCs and Fountain codes. The key part in the new proposed\ud system is that the dynamic range of ADCs can be reduced by\ud discarding the packets which are transmitted over 'bad' sub\ud carriers. Correspondingly, the power consumption in ADCs can be\ud reduced. Also, the new system does not process all the packets but\ud only processes surviving packets. This new error correction layer\ud does not require perfect channel knowledge, so it can be used in a\ud realistic system where the channel is estimated. With this new\ud approach, more than 70% of the energy consumption in the ADC can be\ud saved compared with the conventional IEEE 802.11a WLAN system under\ud the same channel conditions and throughput. The ADC in a receiver\ud can consume up to 50% of the total baseband energy. Moreover, to\ud reduce the overhead of Fountain codes, we apply message passing and\ud Gaussian elimination in the decoder. In this way, the overhead is\ud 3% for a small block size (i.e. 500 packets). Using both methods\ud results in an efficient system with low delay