Interference to cable television due to mobile usage in the Digital Dividend - Analysis

The use of mobile applications in the 800 MHz band, which forms part of the ‘Digital Dividend’, may cause interference to cable TV signals under certain conditions. The new mobile applications (called LTE, Long Term Evolution) use frequency bands also used in cable TV networks. This paper discusses the results of an investigation carried out by the Dutch Radiocommunications Agency and University of Twente. In this investigation an interference model has been derived which shows that the interference probability from mobile applications in the Digital Dividend band is low: on average 5000 Dutch households would experience interference per TV evening. In addition, we propose a number of measures for individual households that can reduce the interference probability to almost zero. Especially better cables and set top boxes or moving the LTE mobile further away from the TV are effective measures

Measuring the service level in the 2.4 GHz ISM band

In this report we provide the findings of the 2.4 GHz service level research. Here service level means the following: can all devices in the 2.4 GHz band fulfill their communication needs. In other words this corresponds to the overall Quality of Service (QoS). The project is a short research exploratory project of about 400 hours in collaboration with Agentschap Telecom, the Dutch Radiocommunications Agency. First of all a survey has been made to investigate which measurement methods can be used to assess the service level in the 2.4 GHz. Here the focus is on IEEE 802.11b/g/n (WiFi) systems. The service level can be measured at several levels of the OSI model: spectrum sensing (physical layer) and packet sniffers (datalink layer). Power level measurements are used to assess the utilization of the 2.4 GHz ISM band. On the other hand packet sniffers are an appropriate method to measure congestion and to pinpoint problems. Secondly, in this project the interferer mechanisms of several sources (microwave, wireless A/V transmitter, Bluetooth, second WiFi network) have been measured in a controlled environment. It turns out that interferers not only increase retry rate, but also trigger unwanted WiFi mechanisms; especially the hidden node mechanism (Request To Send (RTS)/Clear To Send (CTS) packets). So this means that the CTS/RTS control packets, but also the retry rate can be used to identify congestion. The spectrum measurement results allow to identify which interferer source causes congestion. Finally, also a measurement setup is presented that allows to measure the service level. In addition, initial measurements are provided of live environments (college room, office room, city centre). The results show inefficient use of the wireless medium in certain scenarios, due to a large frame rate of management and control packets compared to the data frame rate. In a busy WiFi environment (college room) only 20% of all frames are data frames. Of these data frames only 1/10 are actual data frames as most data frames are so-called null frames; used to keep a WiFi connection alive in power save mode. From all frames about 70% are control frames of which most are ACK frames and in less extend CTS/RTS frames. More research is required to identify the reasons for the high number of control frames. It is likely that there is significant interference, probably due to the many WiFi devices. This is also depicted by the retry frame rate (7%). Combining spectrum sensing with packet sniffing seems to be a good method to assess the service level in the 2.4 GHz ISM band. However, the interferer mechanisms that occur between WiFi networks, WiFi devices and other technologies are complex. More research is needed to enhance the developed proof-of-concept demonstrator and to have a better understanding of the interferer mechanisms in WiFi systems

Non-recognizable error probability in a terrestrial DAB single frequency network

DAB (Digital Audio Broadcasting) is a the European successor of FM radio and it can broadcast besides audio services also other services such as traffic information. In this paper the probability of non-recognized errors in the system is derived for a 8 kbit/s data subchannel using protection level EEP3-A. This is important as data services rely on error-free transmission. It has been shown that in a live DAB network, this probability is very low. For a realistic user scenario, a user will encounter on average a non-recognized packet each 100000 year

Functional Analysis of a SDR Based Bluetooth/HiperLAN Terminal Demonstrator

|In our Software Defined Radio (SDR) project we aim at combining two different types of standards, Bluetooth and HiperLAN/2 on one common hardware platform. HiperLAN/2 is a high-speed Wireless LAN (WLAN) standard, whereas Bluetooth is a low-cost and low-speed Personal Area Network (PAN) standard. An SDR system is a °exible radio system that is re-programmable and reconfigurable by software in order to cope with its multi-service, multi-standard and multi-band environment. Goal of our project is to generate knowledge about designing the front end of an SDR system where especially an approach from both analog and digital perspective is essential.To what extent can we use the HiperLAN/2 receiver hardware for our Bluetooth receiver? In this paper we present a functional architecture that brings the architectural descriptions of both standards to an equal level. This SDR functional architecture is used in the sequel of the project for a number of purposes, of which we mention 1. Definition of reference points (for requirements definition purposes). 2. Definition of interfaces (potential alignment with SDR Forum). 3. Delimitation of our demonstrator (what is it that is going to be built). 4. Identification of inter-standard functional integration challenges

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 HiperLAN/2 case are presented

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

The Exploration of the Software-Defined Radio Concept by Prototyping Transmitter and Receiver Functions on a Digital Signal Processor

An ideal software radio is a system that performs analog-to-digital conversion directly after the antenna and then does all signal processing required in the digital domain on a platform that supports reconguration. Software-defined radio (SDR) is the term used for a more realistic approach in which part of the processing is still done in the analog domain. The use of mobile telephony has shown a spectacular growth in the last 10 years. A side eect of this rapid growth is an excess of mobile system standards. Therefore, the SDR concept is emerging as a potential pragmatic solution. It aims to build flexible radio systems, which are multipleservice, multi-standard, multi-band, re-congurable and reprogrammable, by software. First, this paper presents a global overview of SDR. Furthermore, it explains the implementation of an SDR transmitter and receiver that have been simplied for the purpose of illustration. The source code has been written in C and is running on a DSP evaluation module of Texas Instruments. The algorithms are based on a modied version of the China Wireless Telecommunication Standard (CWTS). The correctness of the implemented system has been verified and measurements of the bit error rate versus the bit-energy-to-noise-energy ratio are reported

Performance evaluation of a combined HiperLAN/2-Bluetooth digital front-end

In our Software-Defined-Radio (SDR) project we aim to combine two receivers (HiperLAN/2 and Bluetooth) on one common platform. In this paper, the main focus is on one of the performance bottlenecks of such a receiver, namely the bandpass filter section in Bluetooth mode. Contributions of inter-symbol interference ISI, adjacent channel interference ACI and noise on the total bit error rate BER are analyzed. The influence of the channel selection filter characteristics on these contributions are researched. Larger values for (for instance) transition bandwidth result in lower order filters that reduce the computational load, which is an important design consideration. This also reduces bit errors caused by ISI, one of the two major contributors to the total BER. On the other hand, lower order filters increase the BER due to ACI. Optimal filter parameters are derived from these trade-offs and applied the system which will be presented