The optimization capacity of the MU-MIMO with channel quality information

Yamindi, Jean-Baptiste; Ji, Hong; Muqing, Wu

doi:10.1109/isce.2012.6241685

Cited by 3 publications

(2 citation statements)

References 3 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…With proper selection of these system parameters, we can exploit bandwidth resources more effectively instead of using a fixed parameter set that provides the best performance only in a worst-case channel condition. [1] Here we will review various measurement made in the mobile receiver in order to ascertain the channel conditions as a function of time. These include Channel Quality Indicator (CQI), Precoder Matrix Indicator (PMI), and Rank Indicator (RI) measurements of which we will take up CQI only.…”

Section: Introductionmentioning

confidence: 99%

Performance Comparison of Modulation Schemes and Adaptive Modulation Scheme with CQI Feedback

Matkar¹,

Jain²

2018

IJSHRE

View full text Add to dashboard Cite

This paper includes a little bit addition to lot of work done to improve the Spectral efficiency of mobile communication system in LTE. The improvement in spectral efficiency is done by increasing data rate through adapting higher order modulation schemes or higher dimension MIMO techniques. But in noisy channel condition, such selection may increase the probability of error, thus leads to lesser throughput. In this Paper, we have optimized the performance of the MIMO trans-receiver by comparing its performance in case of various modulation schemes and Adaptive modulation schemes using the CQI feedback. A comparison graph has been drawn to show the performance comparison on the basis of RMS Error vs SNR dB curve and thus comparing the data rate and error rate for various SNR values for different schemes.

show abstract

Section: Introductionmentioning

confidence: 99%

Performance Comparison of Modulation Schemes and Adaptive Modulation Scheme with CQI Feedback

Matkar¹,

Jain²

2018

IJSHRE

View full text Add to dashboard Cite

show abstract

“…In the literature, the term partial CSI is widely used for any channel information that is different from full CSI (e.g., ). In particular, the term has been used to represent different types of MIMO channel information including the statistical information of the channel such as spatial, frequency, and path correlation (e.g., ), properties of the channel matrix such as rank and precoding matrix indicator(e.g., ), or a part of the channel matrix (e.g., ). In this paper, however, we use a special multiplicative model that decomposes the channel matrix into a known and an unknown.…”

Section: Introductionmentioning

confidence: 99%

Clustered linear precoding for downlink network MIMO systems with partial CSI

Sadeghzadeh

Bahrami

Tran

2016

Wireless Communications

View full text Add to dashboard Cite

We propose two novel clustered linear precoding schemes applicable to network multi-input multi-output systems using only partial channel state information to enhance the sum-rate of the system. Using a channel model that decomposes a multi-input multi-output channel matrix into transmit and receive steering vectors and assuming that only transmit steering vectors are available at the base transmit stations, we, first, propose a regularized channel inversion precoding scheme to enhance the sum-rate assuming only single-antenna users are available in the system. Next, because of the limitation of regularized channel inversion to handle users with multiple receive antennas, a novel block diagonalization method is proposed. We construct the precoding matrices that jointly eliminate inter-cell interference and maximize the sumrate for a given input covariance matrix. Assuming total power constraint and per-base-station power constraints, optimal power allocation schemes are further developed to optimize the sum-rate. We analytically show that the sum-rate increases linearly with the number of users when only single-antenna users are present in the system. Numerical results show that at low signal-to-noise ratios, the block diagonalization precoding outperforms the regularized channel inversion in terms of the bit error rate; while at high signal-to-noise ratios, the regularized channel inversion provides a better performance.Clustered linear precoding for downlink network MIMO systems or a part of the channel matrix (e.g., [27,28]). In this paper, however, we use a special multiplicative model that decomposes the channel matrix into a known and an unknown. We then use this model to derive the proposed partial CSI-based precoders. Related WorkAmong precoding techniques for downlink multiuser systems, regularized channel inversion and block diagonalization (BD) with full CSI have received lots of attention. The recent attempts on the design of regularized channel inversion precoding have mainly focused on maximizing the sum-rate of single-cell and multi-cell systems [29][30][31][32].In [29], optimal power allocation for the case of multiuser multi-input single-output is proposed, and it is shown that, for large number of transmit antennas, the power allocation converges to a waterfilling scheme. In [30], the throughput of a multi-cell downlink network with imperfect CSI is investigated and in [31] and [32], secrecy sum-rate and ergodic secrecy sum-rate of the multiuser MIMO have been studied. In [5] and [9], the BD technique with full CSI, originally proposed for single-cell multi-user MIMO systems [10][11][12], is deployed to design precoder matrices for network MIMO to mitigate the ICI between user equipments (UEs). More recently, the complexity reduction of BD techniques have been investigated in [33][34][35]. In [33] and [34], the authors propose the complexity reduction of BD using a common channel inversion method, QR decomposition, and lattice reduction, while in [35], a generalized zero-forcing precoder is prop...

show abstract

LTE-A uplink antenna solution analysis

Zhou

Guo

2013

2013 8th International Conference on Communications and Networking in China (CHINACOM)

View full text Add to dashboard Cite

The optimization capacity of the MU-MIMO with channel quality information

Cited by 3 publications

References 3 publications

Performance Comparison of Modulation Schemes and Adaptive Modulation Scheme with CQI Feedback

Performance Comparison of Modulation Schemes and Adaptive Modulation Scheme with CQI Feedback

Clustered linear precoding for downlink network MIMO systems with partial CSI

LTE-A uplink antenna solution analysis

Contact Info

Product

Resources

About