Macro-cellular MIMO with dual polarized base station antennas and different spacing

Lindmark, B.; Zetterberg, Per; García-García, L.

doi:10.1049/ic.2007.1325

Cited by 3 publications

(3 citation statements)

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“…In fact, multiple DP and SP antennas are strong candidates to be used in future communication systems such as, e.g., long term evolution (LTE) systems. For example, the measurements reported in [6] show that the use of multiple DP base station antennas yields good communication performance.…”

Section: Introductionmentioning

confidence: 99%

Modeling and Capacity of Polarized MIMO Channels

Coldrey

2008

VTC Spring 2008 - IEEE Vehicular Technology Conference

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In this work the modeling and capacity of a dual polarized (DP) MIMO channel is addressed. The modeling includes channel parameters such as receive and transmit correlation, channel cross-polarization discrimination (XPD), and antenna parameters such as polarization state, polarization parallelity and coupling. The capacity of the DP MIMO channel is evaluated and compared to the capacity of a single polarized (SP) MIMO system. The SP MIMO system with spatially separated antenna sensors has the advantage that it also offers array gain and will therefore during idealized conditions outperform the DP MIMO system. However, in this work it is found that this advantage often is reduced and sometimes even lost when channel and antenna imperfections such as, e.g., correlation, channel XPD, and polarization mismatch are introduced. The main conclusion is that DP antennas might not always yield the best MIMO performance, but instead offer compact antenna solutions for mobile devices and robust performance that is more insensitive to the aforementioned imperfections.

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Section: Introductionmentioning

confidence: 99%

Modeling and Capacity of Polarized MIMO Channels

Coldrey

2008

VTC Spring 2008 - IEEE Vehicular Technology Conference

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“…MIMO propagation characteristics have been thoroughly analyzed in a series of studies under outdoor conditions for dual-polarized antennas [2][3][4][5][6][7]. One study validated the stochastic MIMO channel considering polarization diversity and unbalanced branch power ratio by comparing Monte-Carlo simulations and experimental results of the 4x4 MIMO [2].…”

Section: Introductionmentioning

confidence: 99%

“…Another study analyzed the distance criterion for dualpolarized antennas at both transmitter and receiver sides of a 4x4 line-of-sight (LOS) MIMO system together with the effect of the beam width of the individual elements on the capacity [3]. In study [4], joint analysis of the crosspolarization discrimination (XPD) and the effective spacing between base station antennas was presented when using dual polarized base station antennas in a 4x4 MIMO system. Study [5] presented results from the 2x2 MIMO fixed outdoor channel measurement campaign conducted at 2.48 GHz in the suburban residential areas of San Jose, CA.…”

Section: Introductionmentioning

confidence: 99%

MIMO capacity estimation based on single and dual-polarization MIMO channel measurements

Nanba

Miyazaki

Hirota

et al. 2010

2010 16th Asia-Pacific Conference on Communications (APCC)

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Multiple-Input Multiple-Output (MIMO) wireless system is one of the most promising technologies for providing a large transmission capacity without expanding the frequency band in cellular mobile systems. This paper focuses on 2x2 MIMO capacity estimation through propagation measurements at 2GHz band. The authors conducted the measurement campaign in two regions in Fujimino (Saitama prefecture) and Yokohama (Kanagawa prefecture) Japan. The former is a typical residential area and the latter is an urban area. The paper compares MIMO spatial multiplexing efficiency in terms of the eigenvalue ratio between the single and orthogonal dualpolarization antenna configurations. The eigenvalue ratio is characterized by two parameters. One is cross-polarization discrimination (XPD) and the other is the normalized received signal strength indicator (RSSI), which represents the difference from the RSSI when free space propagation is assumed. It is verified that the MIMO capacity of the dual-polarization can be estimated from just the SNR because the dependency of the eigenvalue ratio on the propagation environment is small. In contrast, that of the single-polarization needs to consider both the eigenvalue ratio and the SNR because the eigenvalue ratios change significantly due to the propagation environment.

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On the Feedback Reduction of Multiuser Relay Networks Using Compressive Sensing

Elkhalil

Eltayeb

Kammoun

et al. 2016

IEEE Trans. Commun.

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In this paper, we propose a feedback reduction scheme for full-duplex relay-aided multiuser networks. The proposed scheme permits the base station (BS) to obtain channel state information (CSI) from a subset of strong users under substantially reduced feedback overhead. More specifically, we cast the problem of user identification and CSI estimation as a block sparse signal recovery problem in compressive sensing (CS). Using existing CS block recovery algorithms, we first obtain the identity of the strong users and then estimate their CSI using the best linear unbiased estimator (BLUE). To minimize the effect of noise on the estimated CSI, we introduce a back-off strategy that optimally backsoff on the noisy estimated CSI and derive the error covariance matrix of the post-detection noise. In addition to this, we provide exact closed form expressions for the average maximum equivalent SNR at the destination user. Numerical results show that the proposed algorithm drastically reduces the feedback air-time and achieves a rate close to that obtained by scheduling schemes that require dedicated error-free feedback from all the network users.

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Macro-cellular MIMO with dual polarized base station antennas and different spacing

Cited by 3 publications

References 0 publications

Modeling and Capacity of Polarized MIMO Channels

Modeling and Capacity of Polarized MIMO Channels

MIMO capacity estimation based on single and dual-polarization MIMO channel measurements

On the Feedback Reduction of Multiuser Relay Networks Using Compressive Sensing

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