A stochastic MIMO radio channel model with experimental validation

Kermoal, J.P.; Schumacher, Laurent; Pedersen, Klaus I.; Mogensen, Preben; Frederiksen, Frank

doi:10.1109/jsac.2002.801223

Cited by 1,220 publications

(668 citation statements)

References 24 publications

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“…Therefore, multiple antenna arrays used in the transmitter and the receiver should be accurately designed to reduce the spatial correlation and achieve higher capacity. In the antenna design process, spatially correlated MIMO channels are typically modeled under certain assumptions about the scattering in the propagation environment and the geometry of the antenna arrays as in [2][3][4][5][6][7][8][9][10][11]. The proper modeling of channel is a challenging task and important part of the antenna design procedure as it can affect the performance of the wireless system under consideration.…”

Section: Introductionmentioning

confidence: 99%

Optimization of Channel Capacity for Indoor Mimo Systems Using Genetic Algorithm

Mangoud¹

2009

PIER C

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Abstract-The geometrical parameters of antenna arrays in a multiple-input multiple-output (MIMO) link that will maximize the ergodic channel capacity of the system are investigated. The problem of selecting the optimum number of the elements at the base station antenna array is also included. The genetic algorithm technique is applied for the optimisation process, using the ergodic capacity as a fitness function. A discrete model based on statistical distribution of the Angle of Arrival (AoA) of the incoming rays is considered. Searching for more compactness in the antenna size and higher system capacity, different array configurations with non-uniform inter-element spacing are considered, such as linear array, circular array and multicircular array (Star) geometries. Numerical examples that illustrate new designs of non-uniform spaced arrays are presented to show the capability of the developed procedures to optimize the capacity of indoor MIMO systems.

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Section: Introductionmentioning

confidence: 99%

Optimization of Channel Capacity for Indoor Mimo Systems Using Genetic Algorithm

Mangoud¹

2009

PIER C

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“…We further assume that the AOD at the Tx can be decomposed from the AOA at the Rx. The latter gives rise to the so-called Kronecker model with separable spatial correlations at the Tx and Rx [59]. However, this assumption was questioned in publications that followed, see e.g., [60] and [61].…”

Section: Slmentioning

confidence: 99%

Generic stochastic modeling of vehicle-to-vehicle wireless channels

Karadimas

Matolak

2014

Vehicular Communications

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We present a generic statistical characterization of the vehicle-to-vehicle (V-V) wireless channel by adopting a stochastic modeling approach. Our approach is based on the doubly underspread (DU) property of non-wide sense stationary uncorrelated scattering (non-WSSUS) wireless channels, with V-V channels pertaining to this category. DU channels exhibit explicit frequency and time intervals over which they are approximated as WSSUS. We call these intervals restricted time interval (RTI) and restricted bandwidth (RBW), and variations taking place inside them are characterized as small scale variations. Large scale variations take place outside RTI and RBW. In this paper, we focus on small scale variations, thus, our modeling finds its applicability within RTI and RBW. As practical V-V channels exhibit rapid

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“…The derivation is similar to the unconstrained NKP problem and therefore omitted; see [24] for further reference. Hence, (26) and (27) represent an approximate solution to (10) with which help we can compute the corresponding far-field radiation pattern, (4) and (5). It is however desirable to obtain exact solutions.…”

Section: Approximate Solution To a Constrained Nkp Problemmentioning

confidence: 99%

“…However, under some special conditions it can still be a good working model, e.g., when the correlation statistics at one end of the link is determined by a local scattering process and is less sensitive to changes at the other end of the link [26,27]. Based on the above model we state the following propositions.…”

Section: An Exact Solution To the Constrained Nkp Problem Under The Amentioning

confidence: 99%

On Some Optimal Mimo Antenna Coefficients in Multipath Channels

Glazunov¹,

Zhang

2011

PIER B

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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.

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A stochastic MIMO radio channel model with experimental validation

Cited by 1,220 publications

References 24 publications

Optimization of Channel Capacity for Indoor Mimo Systems Using Genetic Algorithm

Optimization of Channel Capacity for Indoor Mimo Systems Using Genetic Algorithm

Generic stochastic modeling of vehicle-to-vehicle wireless channels

On Some Optimal Mimo Antenna Coefficients in Multipath Channels

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