2 &amp;#x00D7; 2 MIMO channel characteristics under received power imbalance through indoor propagation measurements

Nanba, Shinobu; Hirota, Yuki; Kishi, Yoji

doi:10.1109/rws.2012.6175353

Cited by 5 publications

(3 citation statements)

References 5 publications

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“…Figure 7 shows the relationship between the Tx antenna correlation and the eigenvalue ratio for received power imbalance G Δ of 0-1 dB, 9-10 dB, and 14-15 dB for all measurement data obtained from the 2 x 2 MIMO propagation experiments using two co-polarized transmitter antennas for the indoor environments described in Section II. The details of the measurement systems and environments are referred to [4]. Figure 7 shows that the eigenvalue ratios decrease, when the received power imbalance increases.…”

Section: A Conventional Methodsmentioning

confidence: 99%

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Channel capacity estimation method for 2 × 2 MIMO considering received power imbalance and antenna correlation

Nanba

Hirota

Kishi

2012

2012 6th European Conference on Antennas and Propagation (EUCAP)

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In cellular systems, optimization of cell coverage planning is advantageous in the deployment of service areas. For this purpose, it is important to adequately estimate MIMO capacity in MIMO wireless systems. In the planning, one requirement is that MIMO channel capacity must be estimated as simply as possible to reduce computation time. We have shown that an eigenvalue ratio, which is a key parameter deriving 2 x 2 MIMO channel capacity, can be estimated from the received power imbalance in a propagation environment where antenna correlation is low [1]. However, the method can cause significant estimation errors in propagation environments with higher antenna correlation. This paper proposes a new method to estimate eigenvalue ratios with a high degree of accuracy considering the antenna correlation as well as the received power imbalance. The method leads to more accurate MIMO channel capacity estimation regardless of the propagation environments.

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Section: A Conventional Methodsmentioning

confidence: 99%

“…This approach is effective in environments with lower antenna correlation. The estimation error, however, increases in areas with higher antenna correlation [4]. Thus, we propose a new method of estimating the eigenvalue ratios in consideration of the Tx antenna correlation and the received power imbalance.…”

Section: Introductionmentioning

confidence: 99%

Channel capacity estimation method for 2 × 2 MIMO considering received power imbalance and antenna correlation

Nanba

Hirota

Kishi

2012

2012 6th European Conference on Antennas and Propagation (EUCAP)

Self Cite

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“…The gain imbalance of the channel matrix deteriorates diversity gain [21]. Thus, it is a trade-off between the correlation and the diversity gain.…”

Section: ) Design Of Precoding For Amplitude Variationmentioning

confidence: 99%

Open-Loop Correlation Reduction Precoding in Overloaded MIMO-OFDM Systems

Matsuoka

Doi

Yabe

et al. 2015

2015 IEEE 82nd Vehicular Technology Conference (VTC2015-Fall)

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This paper proposes an open-loop correlation reduction precoding scheme for overloaded multiple-input multipleoutput (MIMO) orthogonal frequency division multiplexing (OFDM) systems. In overloaded MIMO-OFDM systems, frequency diversity through joint maximum likelihood (ML) decoding suppresses performance degradation owing to spatial signal multiplexing. However, on a line-of-sight (LOS) channel, a channel matrix may have a large correlation between coded symbols transmitted on separate subcarriers. The correlation reduces the frequency diversity gain and deteriorates the signal separation capability. Thus, in the proposed scheme, open-loop precoding in order to reduce the correlation between codewords transmitted on different signal streams is employed at the transmitter of an overloaded MIMO system. The proposed precoding scheme changes the amplitude as well as the phase of the coded symbols transmitted on different subcarriers. Numerical results obtained through computer simulation show that the proposed scheme improves the bit error rate performance on Rician channels.

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Open area 2 × 2 MIMO channel model for 2 GHz low-elevation links with diversity and capacity applications

et al. 2017

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In civil surveillance applications, unmanned aerial vehicles (UAV) are being increasingly used in floods, fires, and law enforcement scenarios. In order to transfer large amounts of information from UAV‐mounted cameras, relays, or sensors, large bandwidths are needed in comparison to those required for remotely commanding the UAV. This demands the use of higher‐frequency bands, in all probability in the vicinity of 2 or 5 GHz. Novel hardware developments need propagation channel models for the ample range of operational scenarios envisaged, including multiple‐input, multiple‐output (MIMO) deployments. These configurations may enable a more robust transmission by increasing either the carrier‐to‐noise ratio statistics or the achievable capacity. In this paper, a 2 × 2 MIMO propagation channel model for an open‐field environment capable of synthesizing a narrowband time series at 2 GHz is described. Maximal ratio combining diversity and capacity improvements are also evaluated through synthetic series and compared with measurement results. A simple flat, open scenario was evaluated based on which other, more complex environments can be modeled.

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2 × 2 MIMO channel characteristics under received power imbalance through indoor propagation measurements

Cited by 5 publications

References 5 publications

Channel capacity estimation method for 2 × 2 MIMO considering received power imbalance and antenna correlation

Channel capacity estimation method for 2 × 2 MIMO considering received power imbalance and antenna correlation

Open-Loop Correlation Reduction Precoding in Overloaded MIMO-OFDM Systems

Open area 2 × 2 MIMO channel model for 2 GHz low-elevation links with diversity and capacity applications

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2 &#x00D7; 2 MIMO channel characteristics under received power imbalance through indoor propagation measurements

Cited by 5 publications

References 5 publications

Channel capacity estimation method for 2 &#x00D7; 2 MIMO considering received power imbalance and antenna correlation

Channel capacity estimation method for 2 &#x00D7; 2 MIMO considering received power imbalance and antenna correlation

Open-Loop Correlation Reduction Precoding in Overloaded MIMO-OFDM Systems

Open area 2 × 2 MIMO channel model for 2 GHz low-elevation links with diversity and capacity applications

Contact Info

Product

Resources

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2 × 2 MIMO channel characteristics under received power imbalance through indoor propagation measurements

Channel capacity estimation method for 2 × 2 MIMO considering received power imbalance and antenna correlation

Channel capacity estimation method for 2 × 2 MIMO considering received power imbalance and antenna correlation