Download presentation

Presentation is loading. Please wait.

Published byPamela Aswell Modified over 4 years ago

1
Capacity of MIMO Channels: Asymptotic Evaluation Under Correlated Fading Presented by: Zhou Yuan University of Houston 10/22/2009

2
Outline Introduction Signal model and assumptions Asymptotic capacity per antenna in correlated fading model Analysis of results Conclusion

3
Introduction MIMO technology Previous work – Consider a random model for the channel (such as Rayleigh-fading channel) – Channel capacity can increase as much as linearly with the minimum number of antennas either at transmitter or receiver – Cannot generally obtain a closed form analytical solution

4
Introduction Analyze asymptotic capacity – Number of transmit and receive antennas are driven to infinity – Ratio between transmit and receive antennas is constant Free Probability Theory – Useful to describe the distribution of eigenvalues of random matrices when their dimensions increase without bound

5
Signal Model Signal model: Channel capacity – This expression does not have a closed analytical form – Need to consider asymptotic expression

6
Signal Model Asymptotic expression of capacity – Using random matrix theory – As the dimensions of the random matrix are driven to infinity, the empirical distribution function of the eigenvectors of some random matrix models tends to a nonrandom quantity c=M/N

7
Capacity Under Correlated Fading Channel In nonasymptotic scenario, only based on numerical evaluation or they can only describe the behavior of the capacity in terms of bounds In asymptotic scenario, be more representative in situations where the number of transmit antennas is of the same order of magnitude as the number of receive ones – Focus on the case where fading correlation arises at the receiver only

8
Correlation at Receive Side Model the channel matrix as: – C: N*N Toeplitz matrix which contains the fading correlation between two receive elements – U: N*M matrix with i.i.d. circular symmetric complex Gaussian entries with zero mean and unit variance The expression of the asymptotic capacity becomes: – where m(z) is the Stieltjes transform of F(x)

9
Correlation at Receive Side Stieltjes transform m(z) is derived using results from Free Probability Theory – Describe the eigenvalue distribution function of a product of infinite- dimensional matrices as a function of the eigenvalue distribution of each matrix – When the dimension of the problem increase without bound, the two matrices become asymptotically free – In this case, we can obtain the asymptotic eigenvalue distribution function of the product of the two matrices from the asymptotic eigenvalue distribution of each one S-transform, which can be obtained from the Stieltjes transform where is the formal inverse of and

10
Correlation at Receive Side Capacity per antenna: where

11
Correlation at Receive Side Fig 1: Comparative representation of the shape of the proposed and the exponential correlation models. Stems: proposed model. Solid line: exponential model that generates the same eigenvalue spread of the covariance matrix (exponential correlation parameter denoted by rho). Dotted line: exponential model that generates the same correlation between consecutive elements (denoted by lambda).

12
Correlation at Transmit Side Model the channel matrix as: Capacity per antenna:

13
Preliminary Analysis Fig 2:Asymptotic capacity per receive antenna.

14
Analysis of Results Fig 3: Asymptotic capacity per receive antenna as a function of Eb/N0 for different values of the correlation parameter u.

15
Analysis of Results Fig 4: Loss in capacity per receive antenna in presence of fading correlation.

16
Analysis of Results Fig 5: Asymptotic capacity per antenna for Eb/N0=10dB.

17
Simulation Results Fig 6: Convergence of the mean value of the capacity per antenna toward its asymptotic value for c=0.5.

18
Conclusion Presented a closed form of the asymptotic uniform power allocation capacity of MIMO systems – Assume correlated fading at one side – The expression is obtained modeling the asymptotic eigenvalue distribution of the fading correlation matrix as a titled semicircular law depending on a parameter that describes the degree of fading correlation between antennas Proposed model is close to an exponentially decaying function Interesting properties: – Fading correlation does not influence the rate of growth with Eb/N0 – Number of transmit antennas increases without bound and number of receive antennas is held constant, the asymptotic spatial efficiency saturates to a constant value that depends on the fading correlation parameter only

19
Questions?

Similar presentations

OK

Chapter 21 R(x) Algorithm a) Anomaly Detection b) Matched Filter.

Chapter 21 R(x) Algorithm a) Anomaly Detection b) Matched Filter.

© 2018 SlidePlayer.com Inc.

All rights reserved.

To make this website work, we log user data and share it with processors. To use this website, you must agree to our Privacy Policy, including cookie policy.

Ads by Google