A survey on OFDM channel estimation techniques based on denoising strategies

Sure, Pallaviram; Bhuma, Chandra Mohan

doi:10.1016/j.jestch.2016.09.011

Cited by 51 publications

(35 citation statements)

References 28 publications

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“…The proof of the mean-square estimation error per antenna is given in Appendix B. The analytical mean-square estimation error expression (45) is useful for system design and performance evaluation purposes [83].…”

Section: Proposed Channel Estimatormentioning

confidence: 99%

On the Application of Massive MIMO Systems to Machine Type Communications

et al. 2019

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This paper evaluates the feasibility of applying massive multiple-input multiple-output (MIMO) to tackle the uplink mixed-service communication problem. Under the assumption of an available physical narrowband shared channel, devised to exclusively consume data traffic from machine type communications (MTC) devices, the capacity (i.e., number of connected devices) of MTC networks and, in turn, that of the whole system, can be increased by clustering such devices and letting each cluster share the same time-frequency physical resource blocks. Following this research line, we study the possibility of employing sub-optimal linear detectors to the problem and present a simple and practical channel estimator that works without the previous knowledge of the large-scale channel coefficients. Our simulation results suggest that the proposed channel estimator performs asymptotically, as well as the MMSE estimator, with respect to the number of antennas and the uplink transmission power. Furthermore, the results also indicate that, as the number of antennas is made progressively larger, the performance of the sub-optimal linear detection methods approaches the perfect interference-cancellation bound. The findings presented in this paper shed light on and motivate for new and exciting research lines toward a better understanding of the use of massive MIMO in MTC networks. INDEX TERMS Large-scale antenna systems, 5G networks, machine type communications, channel estimation, linear detection.

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Section: Proposed Channel Estimatormentioning

confidence: 99%

On the Application of Massive MIMO Systems to Machine Type Communications

et al. 2019

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“…For the LM, the IM which performs impersonation attacks also transmits a pilot signal to estimation channels between the DCU and the IM. Then, as shown in [57], the channel estimation errors which can be influenced by noises can sufficiently be reduced by using channel estimation techniques based on denoising strategies. So, the channels can be estimated with negligibly small error.…”

Section: B Cs Based Physical Layer Authenticationmentioning

confidence: 99%

A Unified Approach for Compression and Authentication of Smart Meter Reading in AMI

2019

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In this paper, we propose a unified approach for compression and authentication of smart meter reading in advanced metering infrastructure (AMI). In general, smart meters are urged to send sampled reading signals at a high rate for high-quality services. Meanwhile, power reading signals have to be authenticated to prevent impersonation attacks, which can cause serious economic loss. However, the security in smart grids faces more challenges than conventional human-type communications because of limited hardware resources of a smart meter (e.g., small memory). Motivated by these problems, we study simultaneous compression and authentication for power reading signals in multicarrier systems based on the notion of compressive sensing (CS). The CS-based compression and authentication method are applied to empirically modeled signals with a shared secret key, a measurement matrix in CS between a data concentrator unit (DCU) and a legitimate smart meter. In particular, for authentication, the residual error of a received signal at the DCU is used as a test statistic for hypothesis testing, which determines whether the signal is a legitimate signal or an intrusion signal in the proposed approach. Through the analysis and simulation results, we demonstrate that the CS-based compression approach can be applied to smart meter reading with good energy efficiency. In addition, it is shown that the proposed scheme can obtain a low authentication error probability under reasonable conditions. For example, when the number of subcarriers is 64, the DCU can distinguish legitimate and intrusion smart meters with a probability of 1 − P E , where P E ≤ 10 −4. INDEX TERMS Authentication, compression, compressive sensing, advanced metering infrastructure.

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“…The estimation of the channel for block-type technique arrangement can be based on Least Square (LS) or Minimum Mean-Square Error (MMSE) algorithms. LS and MMSE algorithms are used for obtaining channel information at pilot subcarriers [17].…”

Section: Wireless Channel Estimation and Interpolation Techniques In mentioning

confidence: 99%

Wireless channel estimation in OFDM systems based on collaborative filtering techniques

Švedek

Kurdija

Ilić

2019

Journal of Electrical Engineering

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In this paper, a new channel estimation algorithm in Orthogonal Frequency Division Multiplexing (OFDM) systems is proposed. The proposed algorithm is suitable for cases with low density of pilot sub-carriers, where standard interpolation methods (linear, second order and cubic spline interpolation) are inaccurate. The algorithm improves the interpolation methods by employing memory based collaborative filtering (CF) techniques which are less sensitive to the number and location of the pilot subcarriers. CF algorithms are usually used in the context of recommender systems (e-commerce) for predictions of the unknown user-item ratings based on known values of similar users. The advantage of CF is the ability to e ciently produce quality predictions with highly sparse data. Computer simulations are used to verify the proposed channel estimation algorithm and demonstrate that the proposed algorithm improves predictive accuracy metrics, such as Root Mean Squared Error (RMSE), compared to usual estimation methods.

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A survey on OFDM channel estimation techniques based on denoising strategies

Cited by 51 publications

References 28 publications

On the Application of Massive MIMO Systems to Machine Type Communications

On the Application of Massive MIMO Systems to Machine Type Communications

A Unified Approach for Compression and Authentication of Smart Meter Reading in AMI

Wireless channel estimation in OFDM systems based on collaborative filtering techniques

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