An Autoregressive Doppler Spread Estimator for Fading Channels

Huang, Pengda; Rajan, Dinesh; Camp, Joseph

doi:10.1109/wcl.2013.091113.130593

Cited by 7 publications

(4 citation statements)

References 13 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Massive multiple-input multiple-output (M-MIMO), together with other technologies, is a auspicious technology to meet high data rate, ultra-low latency, broader coverage 5G system requirements [ 5 ]. M-MIMO can also reinforce the spectrum and power efficiencies [ 6 , 7 , 8 ]. It also increases the throughput of wireless networks.…”

Section: Introductionmentioning

confidence: 99%

A Low Complexity Near-Optimal Iterative Linear Detector for Massive MIMO in Realistic Radio Channels of 5G Communication Systems

Albreem

Alsharif

Kim

2020

Entropy

View full text Add to dashboard Cite

Massive multiple-input multiple-output (M-MIMO) is a substantial pillar in fifth generation (5G) mobile communication systems. Although the maximum likelihood (ML) detector attains the optimum performance, it has an exponential complexity. Linear detectors are one of the substitutions and they are comparatively simple to implement. Unfortunately, they sustain a considerable performance loss in high loaded systems. They also include a matrix inversion which is not hardware-friendly. In addition, if the channel matrix is singular or nearly singular, the system will be classified as an ill-conditioned and hence, the signal cannot be equalized. To defeat the inherent noise enhancement, iterative matrix inversion methods are used in the detectors’ design where approximate matrix inversion is replacing the exact computation. In this paper, we study a linear detector based on iterative matrix inversion methods in realistic radio channels called QUAsi Deterministic RadIo channel GenerAtor (QuaDRiGa) package. Numerical results illustrate that the conjugate-gradient (CG) method is numerically robust and obtains the best performance with lowest number of multiplications. In the QuaDRiGA environment, iterative methods crave large n to obtain a pleasurable performance. This paper also shows that when the ratio between the user antennas and base station (BS) antennas ( β ) is close to 1, iterative matrix inversion methods are not attaining a good detector’s performance.

show abstract

Section: Introductionmentioning

confidence: 99%

A Low Complexity Near-Optimal Iterative Linear Detector for Massive MIMO in Realistic Radio Channels of 5G Communication Systems

Albreem

Alsharif

Kim

2020

Entropy

View full text Add to dashboard Cite

show abstract

“…The restrictions that cause path loss and multipath such as noise, distorsion, inter symbol interference are results of relative motion between the transmitter and receiver (Goldsmith, 2005). There are many schemes of Doppler spread estimation such as level crossing rate (Chen et al, 2011), covariance (Huang et al, 2013), power spectral density (Muralidhar et al, 2007) and maximum probability (Bellilil and Affes, 2013). Fading models work depend on assumption that the total fading arises from set of uncorrelated partial signal which have identically distributed of amplitudes and uniformly distributed of random phases (Xiao et al, 2003(Xiao et al, , 2006.…”

Section: Introductionmentioning

confidence: 99%

Doppler fading communication channel performance simulation

Ahmed¹

2017

Int. J. Phys. Sci.

View full text Add to dashboard Cite

Fading is commonly used to describe the properties of the communication channel. Large efforts have been made to describe characteristics of the channel in wireless communication system. The performance of wireless signal propagation in a conventional environment needs Doppler fading channel schemes by assuming a perfect knowledge about the channel frequency response at both the transmitter and the receiver sides. Two models were used to depict the characteristics of Doppler fading channel in term of source velocity, where the first is free space transmission model consists of two antennas at a given distance (r) to calculate the received signal strength for transmission links at relative motion between the transmitter and receiver antennas. The second model is simulation based on Matlab (2013B) to compute and plot the received signal envelope taking into account the source velocity over the multipath fading. The analysis and employing the information of Doppler fading can enhance the characteristics of channel estimation.

show abstract

“…As shown in the generation of fading channels [16]- [18], fading channel is indeed a stationary random process which allows us to predict a channel state based on its previous several observations. This model is also used in the estimation of the channel state information [19]. The difference of a prediction versus its real channel state is usually called as the innovation of a channel.…”

Section: Introductionmentioning

confidence: 99%

On Channel State Feedback Model and Overhead in Theoretical and Practical Views

Luo

2017

Preprint

View full text Add to dashboard Cite

Channel state feedback plays an important role to the improvement of link performance in current wireless communication systems, and even more in the next generation. The feedback information, however, consumes the uplink bandwidth and thus generates overhead. In this paper, we investigate the impact of channel state feedback and propose an improved scheme to reduce the overhead in practical communication systems. Compared with existing schemes, we introduce a more accurate channel model to describe practical wireless channels and obtain the theoretical lower bounds of overhead for the periodical and aperiodical feedback schemes. The obtained theoretical results provide us the guidance to optimise the design of feedback systems, such as the number of bits used for quantizing channel states. We thus propose a practical feedback scheme that achieves low overhead and improved performance over currently widely used schemes such as zero holding. Simulation experiments confirm its advantages and suggest its potentially wide applications in the next generation of wireless systems.

show abstract

An Autoregressive Doppler Spread Estimator for Fading Channels

Cited by 7 publications

References 13 publications

A Low Complexity Near-Optimal Iterative Linear Detector for Massive MIMO in Realistic Radio Channels of 5G Communication Systems

A Low Complexity Near-Optimal Iterative Linear Detector for Massive MIMO in Realistic Radio Channels of 5G Communication Systems

Doppler fading communication channel performance simulation

On Channel State Feedback Model and Overhead in Theoretical and Practical Views

Contact Info

Product

Resources

About