Effective SNR mapping for link error prediction in OFDM based systems

Sandanalakshmi, R.; Palanivelu, T.G.; Manivannan, K.

doi:10.1049/ic:20070699

Cited by 19 publications

(13 citation statements)

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“…Figure 3 shows the SISO AWGŅ BLER curves the link performance model utilizes [7]. The Exponential Effective Signal to Interference and Noise Ratio Mapping (EESM) [24], [25], [26] is the method currently used to obtain a TB effective SINR γ eff which can be used Fig. 4.…”

Section: Link Performance Modelmentioning

confidence: 99%

System Level Simulation of LTE Networks

Ikuno

Wrulich

Rupp

2010

2010 IEEE 71st Vehicular Technology Conference

430

206

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In order to evaluate the performance of new mobile network technologies, system level simulations are crucial. They aim at determining whether, and at which level predicted link level gains impact network performance. In this paper we present a MATLAB computationally efficient LTE system level simulator. The simulator is offered for free under an academic, noncommercial use license, a first to the authors' knowledge. The simulator is capable of evaluating the performance of the Downlink Shared Channel of LTE SISO and MIMO networks using Open Loop Spatial Multiplexing and Transmission Diversity transmit modes. The physical layer model is based on the postequalization SINR and provides the simulation pre-calculated "fading parameters" representing each of the individual interference terms. This structure allows the fading parameters to be pregenerated offline, vastly reducing computational complexity at run-time.

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Section: Link Performance Modelmentioning

confidence: 99%

System Level Simulation of LTE Networks

Ikuno

Wrulich

Rupp

2010

2010 IEEE 71st Vehicular Technology Conference

430

206

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“…The EESM mapping is derived from the Chernoff union bound for bit error rate (BER). An EESM is used to map the instantaneous channel quality into a scalar value of SINR e f f and then, it will be used to find the estimated BLER from the basic AWGN equivalent link level performance [39]. The mapping algorithm can be expressed as…”

Section: Sinr-cqi Mappingmentioning

confidence: 99%

An Adaptive Threshold Feedback Compression Scheme Based on Channel Quality Indicator (CQI) in Long Term Evolution (LTE) System

Abdulhasan

Salman

et al. 2015

Wireless Pers Commun

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Channel quality indicator (CQI) feedback in long-term evolution (LTE) system is an essential technique in describing the instantaneous channel state information. The CQI calculations highly depend on the accuracy of the channel estimation process in order to assign appropriate modulation and coding scheme. However, one of the critical issues affecting the LTE system performance is obtaining the CQI for each transmission period which will inevitably cost many resources. Therefore, an appropriate method for reducing CQI feedback overhead along with accurate channel estimation technique is required to manage the allocated resources and obtains significant improvements in system performance. In this paper, an adaptive threshold feedback compression scheme based on CQI scheme is proposed to obtain better system performance in terms of system throughput and error rate in LTE system. This proposed adaptive scheme dynamically adapts its threshold level to the signal to noise ratio variations, thus increasing the throughput and reducing the CQI feedback overhead. Results show that the proposed CQI based adaptive threshold feedback compression scheme enhances the tradeoff between system throughput and block error rate.

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“…In this method, a set of subcarrier SINR (γ k ) is mapped into an effective SINR (γ ef f ). The effective SINR is then used to find an estimate of the error probability from the link level performance [6]. It has been proved that EESM could provide an optimistic estimate of the OFDM performance.…”

Section: A System Modelmentioning

confidence: 99%

“…The main contribution of this paper is to present a novel EESM-based fingerprint algorithm to indicate Wi-Fi signal received at a fixed location point. Using EESM (Exponential Effective SINR mapping) [6] as the indoor location fingerprint can effectively reduce the multipath effect as it is a derivation of channel estimation. EESM-based fingerprint not only is more stable but also effectively reduces the multipath effect caused by indoor environment.…”

Section: Introductionmentioning

confidence: 99%

EESM-based fingerprint algorithm for Wi-Fi indoor positioning system

Wang

Huang

et al. 2013

2013 IEEE/CIC International Conference on Communications in China (ICCC)

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In recent years, great improvements took place in smartphone industry. Along with the development of cloud services and web applications, lots of developers also take great effort on developing smartphone applications. Among various applications related to social networks, LBS (Location Based Service) is the key technique which is the basic for social interactive activities. While GPS (global positioning system) works well enough outdoors, Wi-Fi RSS (receive signal strength)-based fingerprinting system is the most promising solution for indoors. A novel EESM-based fingerprint algorithm which improves the positioning performance by involving channel estimation for creating more robust fingerprints is proposed in this paper. Moreover, a cloud computing based indoor positioning system is also introduced for evaluating performances. Both simulations and experiments show that EESM-based fingerprints are more stable and representative in the multipath indoor environments. An up to 30% reduction in error distance in a classic indoor positioning system using k-NN matching algorithm is provided by our proposed EESM-based fingerprints.

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Effective SNR mapping for link error prediction in OFDM based systems

Cited by 19 publications

References 0 publications

System Level Simulation of LTE Networks

System Level Simulation of LTE Networks

An Adaptive Threshold Feedback Compression Scheme Based on Channel Quality Indicator (CQI) in Long Term Evolution (LTE) System

EESM-based fingerprint algorithm for Wi-Fi indoor positioning system

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