Wireless communication systems with-spatial diversity: a volumetric model

Hanlen, Leif; Fu, Minyue

doi:10.1109/twc.2006.1576537

Cited by 43 publications

(51 citation statements)

References 20 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…This approximation, made already by various authors [12], [9], [14], [15] in different contexts, allows us to derive an upper bound on S, and correspondingly, a lower bound on the spatial degrees of freedom. In addition, we provide in the Appendix a rigorous derivation of the lower bound, which does not make use of the approximation.…”

Section: Lemma 24mentioning

confidence: 83%

“…Such physical constraints prevent MIMO capacity from increasing indefinitely with M . The impact of correlated fading [3], [4], [5], [6], [7], the scattering environment [8], [9] and antenna coupling [10], [11] on MIMO capacity was studied by a large body of follow-up research, which also provided a characterization of the inherent spatial degrees of degrees of freedom in a MIMO system as a function of the area and the geometry of the antenna arrays and the angular spread of the physical environment [12], [13], [14], [15].…”

Section: Introductionmentioning

confidence: 99%

“…Mathematically, our approach differs significantly from existing results studying the spatial degrees of freedom of classical MIMO channels. While such results (for example, see [12], [14], [15]) are based on studying the singular values of the continuous propagation operator under approximations for the regime where d ≫ √ A c , our analysis is mathematically rigorous and is based on random matrix analysis.…”

mentioning

confidence: 99%

See 2 more Smart Citations

Spatial Degrees of Freedom of Large Distributed MIMO Systems and Wireless Ad Hoc Networks

Özgür

Lévêque

Tse

2013

IEEE J. Select. Areas Commun.

View full text Add to dashboard Cite

Abstract-We consider a large distributed MIMO system where wireless users with single transmit and receive antenna cooperate in clusters to form distributed transmit and receive antenna arrays. We characterize how the capacity of the distributed MIMO transmission scales with the number of cooperating users, the area of the clusters and the separation between them, in a line-of-sight propagation environment. We use this result to answer the following question: can distributed MIMO provide significant capacity gain over traditional multi-hop in large adhoc networks with n source-destination pairs randomly distributed over an area A? Two diametrically opposite answers [24] and [26] have emerged in the current literature. We show that neither of these two results are universal and their validity depends on the relation between the number of users n and √ A/λ, which we identify as the spatial degrees of freedom in the network. λ is the carrier wavelength. When √ A/λ ≥ n, there are n degrees of freedom in the network and distributed MIMO with hierarchical cooperation can achieve a capacity scaling linearly in n as in [24], while capacity of multihop scales only as √ n. On the other hand, when √ A/λ ≤ √ n as in [26], there are only √ n degrees of freedom in the network and they can be readily achieved by multihop. Our results also reveal a third regime whereHere, the number of degrees of freedom are smaller than n but larger than what can be achieved by multi-hop. We construct scaling optimal architectures for this intermediate regime.

show abstract

Section: Lemma 24mentioning

confidence: 83%

Section: Introductionmentioning

confidence: 99%

mentioning

confidence: 99%

See 1 more Smart Citation

Spatial Degrees of Freedom of Large Distributed MIMO Systems and Wireless Ad Hoc Networks

Özgür

Lévêque

Tse

2013

IEEE J. Select. Areas Commun.

View full text Add to dashboard Cite

show abstract

“…These prior studies have shown relevant findings concerning the effects of mutual coupling on MIMO system performance. Moreover, a few papers describe the optimal antenna coefficients for MIMO systems [13][14][15].…”

Section: Introductionmentioning

confidence: 99%

On Some Optimal Mimo Antenna Coefficients in Multipath Channels

Glazunov¹,

Zhang

2011

PIER B

View full text Add to dashboard Cite

Abstract-This paper derives some optimum transmit and receive antenna coefficients in wireless multipath channels based on the spherical vector wave multimode expansion of the multiple-input multiple-output (MIMO) channel matrix.The derived antenna coefficients satisfy the following specific optimization criteria: (i) maximum MIMO mean effective link gain (link MEG) based on the multimode channel realizations or (ii) maximum MIMO link MEG based on the multimode correlation matrix or (iii) correlation minimization by diagonalization of the MIMO full-correlation matrix. It is shown that the proposed approach leads to matrix equations belonging to the nearest Kronecker product (NKP) problem family, which in general have no trivial solution. However, we show that exact solutions are provided to the posed NKP problems under the assumption of the Kronecker model for the MIMO full-correlation matrix. The results are illustrated by numerical examples. The proposed approach is a complement to existing antenna pattern analysis methods.

show abstract

“…There have been other papers aiming to describe the interaction between the antennas and the channel in terms of multimode expansions [25], [26], [24], [23], [20], [19], [13], [14]. However, these approaches are restricted to the scalar case, where the polarization characteristics of the channel are omitted.…”

Section: Introductionmentioning

confidence: 99%