6,222 research outputs found

    Channel Sounding for the Masses: Low Complexity GNU 802.11b Channel Impulse Response Estimation

    Full text link
    New techniques in cross-layer wireless networks are building demand for ubiquitous channel sounding, that is, the capability to measure channel impulse response (CIR) with any standard wireless network and node. Towards that goal, we present a software-defined IEEE 802.11b receiver and CIR estimation system with little additional computational complexity compared to 802.11b reception alone. The system implementation, using the universal software radio peripheral (USRP) and GNU Radio, is described and compared to previous work. By overcoming computational limitations and performing direct-sequence spread-spectrum (DS-SS) matched filtering on the USRP, we enable high-quality yet inexpensive CIR estimation. We validate the channel sounder and present a drive test campaign which measures hundreds of channels between WiFi access points and an in-vehicle receiver in urban and suburban areas

    Reducing the effects of intersymbol interference in diffuse DPIM optical wireless systems

    Get PDF
    The paper investigates the performance of digital pulse interval modulation (DPIM) in the presence of multipath propagation and additive white Gaussian noise. To combat intersymbol interference (ISI), guard slots and a nonlinear equaliser have been introduced. The average optical power requirements (AOPR) due to ISI for cases with/without guard slots and with equaliser are analysed using a ceilingbounce model. Results obtained show that in the absence of equalisation, DPIM without guard slot offers a lower AOPR compared with on–off keying (OOK). Introducing guard slots gives a further reduction in AOPR by up to 4 dB due to the reduced duty cycle of the DPIM signal. The performance of DPIM without guard slot but using an equaliser is found to be significantly better than DPIM with guard slots on a channel with severe ISI

    Wavelet transform - artificial neural network receiver with adaptive equalisation for a diffuse indoor optical wireless OOK link

    Get PDF
    This paper presents an alternative approach for signal detection and equalization using the continuous wavelet transform (CWT) and the artificial neural network (ANN) in diffuse indoor optical wireless links (OWL). The wavelet analysis is used for signal preprocessing (feature extraction) and the ANN for signal detection. Traditional receiver architectures based on matched filter (MF) experience significant performance degradation in the presence of artificial light interference (ALI) and multipath induced intersymbol interference (ISI). The proposed receiver structure reduces the effect of ALI and ISI by selecting a particular scale of CWT that corresponds to the desired signal and classifying the signal into binary 1 and 0 based on an observation vector. By selecting particular scales corresponding to the signal, the effect of ALI is reduced. We show that there is little variation when using 30 and 5 neurons in the first layer, with one layer ANN model showing a consistently worse BER performance than other models, whilst the 15 neuron model show some behaviour anomalies from a BER of approximately 10-3. The simulation results show that the Wavelet-ANN architecture outperforms the traditional MF based receiver even with the filter is matched to the ISI affected pulse shape. The Wavelet-ANN receiver is also capable of providing a bit error rate (BER) performance comparable to the equalized forms of traditional receiver structure

    Multi Detector Fusion of Dynamic TOA Estimation using Kalman Filter

    Full text link
    In this paper, we propose fusion of dynamic TOA (time of arrival) from multiple non-coherent detectors like energy detectors operating at sub-Nyquist rate through Kalman filtering. We also show that by using multiple of these energy detectors, we can achieve the performance of a digital matched filter implementation in the AWGN (additive white Gaussian noise) setting. We derive analytical expression for number of energy detectors needed to achieve the matched filter performance. We demonstrate in simulation the validity of our analytical approach. Results indicate that number of energy detectors needed will be high at low SNRs and converge to a constant number as the SNR increases. We also study the performance of the strategy proposed using IEEE 802.15.4a CM1 channel model and show in simulation that two sub-Nyquist detectors are sufficient to match the performance of digital matched filter

    Performance of the wavelet-transform-neural network based receiver for DPIM in diffuse indoor optical wireless links in presence of artificial light interference

    Get PDF
    Artificial neural network (ANN) has application in communication engineering in diverse areas such as channel equalization, channel modeling, error control code because of its capability of nonlinear processing, adaptability, and parallel processing. On the other hand, wavelet transform (WT) with both the time and the frequency resolution provides the exact representation of signal in both domains. Applying these signal processing tools for channel compensation and noise reduction can provide an enhanced performance compared to the traditional tools. In this paper, the slot error rate (SER) performance of digital pulse interval modulation (DPIM) in diffuse indoor optical wireless (OW) links subjected to the artificial light interference (ALI) is reported with new receiver structure based on the discrete WT (DWT) and ANN. Simulation results show that the DWT-ANN based receiver is very effective in reducing the effect of multipath induced inter-symbol interference (ISI) and ALI

    Chaos-based wireless communication resisting multipath effects

    Get PDF
    This work is supported by NSFC (China) under Grants No. 61401354, No. 61172070, and No. 61502385; by the Innovative Research Team of Shaanxi Province under Grant No. 2013KCT-04; and by Key Basic Research Fund of Shaanxi Province under Grant No. 2016JQ6015.Peer reviewedPublisher PD

    Bit error performance of diffuse indoor optical wireless channel pulse position modulation system employing artificial neural networks for channel equalisation

    Get PDF
    The bit-error rate (BER) performance of a pulse position modulation (PPM) scheme for non-line-of-sight indoor optical links employing channel equalisation based on the artificial neural network (ANN) is reported. Channel equalisation is achieved by training a multilayer perceptrons ANN. A comparative study of the unequalised `soft' decision decoding and the `hard' decision decoding along with the neural equalised `soft' decision decoding is presented for different bit resolutions for optical channels with different delay spread. We show that the unequalised `hard' decision decoding performs the worst for all values of normalised delayed spread, becoming impractical beyond a normalised delayed spread of 0.6. However, `soft' decision decoding with/without equalisation displays relatively improved performance for all values of the delay spread. The study shows that for a highly diffuse channel, the signal-to-noise ratio requirement to achieve a BER of 10−5 for the ANN-based equaliser is ~10 dB lower compared with the unequalised `soft' decoding for 16-PPM at a data rate of 155 Mbps. Our results indicate that for all range of delay spread, neural network equalisation is an effective tool of mitigating the inter-symbol interference
    corecore