Error Probabilities for Radio Transmissions of MC-CDMA based W-LANs

Orfanos, G.; Habetha, Jörg; Butsch, W.

doi:10.1109/vetecs.2005.1543612

Cited by 7 publications

(3 citation statements)

References 10 publications

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“…• Finally, three FUs model decoding errors of incoming compound based on the indicated SINR: First, an ErrorModelling FU calculates the PER based on the SINR, the selected MCS, the number of spatial streams and receive antennas and the compound length (detailed description and further analysis can be found in [20,19]; the MIMO model is described in [14,18]). Then, a CRC FU drops compounds according to the PER.…”

Section: The Wifimac Phy Layermentioning

confidence: 99%

Evaluation of IMT-Advanced Scenarios using the open Wireless Network Simulator

Max

Bultmann

Jennen

et al. 2010

Proceedings of the 3rd International ICST Conference on Simulation Tools and Techniques

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With the commence of the IMT-Advanced (IMT-A) submission and evaluation process, the vague term "4th generation wireless networks" moves towards existing standards, technologies and hardware. A significant part of the evaluation process is based on the system level simulation of reference scenarios.In this paper, we present how the open Wireless Network Simulator (openWNS), developed in the last 5 years at the department of Communication Networks (ComNets) at RWTH Aachen University, can be used to study protocols of wireless networks. Due to the complexity of IMT-A candidate systems, the features of openWNS are described by means of the lightweight WiFiMAC. This module provides the functions of IEEE 802.11, including amendment n.On this basis, the following details of the simulator are explained: (a) the modular simulation framework for protocol stack development, (b) the WiFiMAC module, (c) simulator calibration to ensure the reliability of the results and (d) the simulation of urban-micro scenarios based on the IMT-A evaluation guidelines.

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Section: The Wifimac Phy Layermentioning

confidence: 99%

Evaluation of IMT-Advanced Scenarios using the open Wireless Network Simulator

Max

Bultmann

Jennen

et al. 2010

Proceedings of the 3rd International ICST Conference on Simulation Tools and Techniques

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“…We use the method described in [5] for PER calculation. PER depends, among other parameters, on the received SNR.…”

Section: B Per Calculationmentioning

confidence: 99%

MIMO Link Modeling for System Level Simulations

Mirković

Orfanos

Reumerman

2006

2006 IEEE 17th International Symposium on Personal, Indoor and Mobile Radio Communications

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MIMO (Multiple Input -Multiple output) systems apply multiple antennas to increase signal to noise ratio (SNR), reduce interference and/or send multiple streams simultaneously over a single channel. Besides increasing the data rate of the physical layer (PHY), benefits can be achieved with cross-layer optimization approach exploiting the layered structure of the channel.In this paper we focus on MIMO schemes with multiplexing and/or diversity gain and present a link model for system level simulations. The model maps total SNR to achievable link level throughput, both per spatial subchannel and cumulative. The model can be combined with an arbitrary coding and modulation scheme and is abstract enough to be applied to any system protocol, fulfilling the given conditions about channel propagation characteristics.

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“…As all this devices operate in the same frequency band, interference from other devices becomes a major issue whenever they operate nearby. In our previous work [19] and from literature performance of WLAN in presence of Bluetooth, Zigbee interference [5][6][7][8][9][10][11][12][13][14] can be found.…”

Section: Introductionmentioning

confidence: 99%

Performance Analysis of MQAM-OFDM Based WLAN in Presence of Zigbee Interference in AWGN and Rayleigh Fading Channel

Roy

Jamadagni

2009

2009 Sixth International Conference on Information Technology: New Generations

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In this paper we give the performance of MQAM OFDM based WLAN in presence of single and multiple channels Zigbee interference. An analytical model for getting symbol error rate (SER) in presence of single and multiple channel Zigbee interference in AWGN and Rayleigh fading channel for MQAM OFDM system is given. Simulation results are compared with analytical symbol error rate (SER) of the MQAM-OFDM system. For analysis we have modeled the Zigbee interference using the power spectral density (PSD) of OQPSK modulation and finding the average interference power for each sub-carrier of the OFDM system. Then we have averaged the SER over all WLAN sub-carriers. Simulations closely match with the analytical models. It is seen from simulation and analytical results that performance of WLAN is severely affected by Zigbee interference. Symbol error rate (SER) for 16QAM and 64QAM OFDM system is of order of 10 -2 for SIR (signal to interference ratio) of 20dB and 30dB respectively in presence of single Zigbee interferer inside the WLAN frequency band for Rayleigh fading channel. For SIR values more than 30dB and 40dB the SER approaches the SER without interference for 16QAM and 64QAM OFDM system respectively.

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Error Probabilities for Radio Transmissions of MC-CDMA based W-LANs

Cited by 7 publications

References 10 publications

Evaluation of IMT-Advanced Scenarios using the open Wireless Network Simulator

Evaluation of IMT-Advanced Scenarios using the open Wireless Network Simulator

MIMO Link Modeling for System Level Simulations

Performance Analysis of MQAM-OFDM Based WLAN in Presence of Zigbee Interference in AWGN and Rayleigh Fading Channel

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