Quantifying diversity and correlation in Rayleigh fading MIMO communication systems

Ivrlač, Michel T.; Nossek, Josef A.

doi:10.1109/isspit.2003.1341084

Cited by 33 publications

(24 citation statements)

References 4 publications

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“…Therefore, fewer correlations between channel coefficients lead to less fluctuation in the received signal, then link reliability can be expected. The diversity gain can limit the amount of variation in the received signal which can be computed by diversity measurement (D div ) as [27] …”

Section: Spatial Diversity Gainmentioning

confidence: 99%

“…As a result, expressions (22) and (27) are given for diversity gain at downlink and uplink channels respectively, which are the same expression, but in fact they have different statistical characteristics, where at the downlink side the transmission from the base station in any cell to its K terminals suffering interference from transmissions of the base stations in other cells to their own K terminals. While at the uplink side, the transmission from the terminal in any cell to its base station is suffering the interferences from the transmissions of terminals in the other cells to their base stations.…”

Section: Uplink Sidementioning

confidence: 99%

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Analysis and Evaluation of Performance Gains and Tradeoffs for Massive MIMO Systems

Jabbar

2016

Applied Sciences

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Abstract:Massive MIMO technique offers significant performance gains for the future of wireless communications via improving the spectral efficiency, energy efficiency and the channel quality with simple linear processing such as maximum-ratio transmission (MRT) or zero-forcing (ZF) by providing each user a large degree of freedom. In this paper, the system performance gains are studied in a multi-cell downlink massive MIMO system under the main considerations such as perfect channel estimation, imperfect channel estimation and the effect of interference among cells due to pilot sequences contamination. Then, mathematical expressions are derived for these gains i.e., spatial multiplexing gain, array gain and spatial diversity gain. After that, essential tradeoffs among these gains are considered under the effect of non-orthogonal interference, these tradeoffs are: spatial diversity gain vs. spatial multiplexing gain and array gain vs. spatial multiplexing gain. Simulation results show that the unbounded number of base station antennas boosts the array gain through concentrating the energy to spatial directions where users are sited, hence diminishing loss in array gain due to pilot contamination. The simulation results reveal also that massive MIMO strengthens the spatial multiplexing gain through increasing the number of served users via the same system resources in spite the effect of inter-cell interference. Finally, the spatial diversity gain is measured in term of outage probability and the simulation results show that raising the number of antennas will improve the outage probability. Meanwhile increasing the number of served users will lead to degrade the outage probability per user due to non-orthogonal interference from other cells.

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Section: Spatial Diversity Gainmentioning

confidence: 99%

Section: Uplink Sidementioning

confidence: 99%

Analysis and Evaluation of Performance Gains and Tradeoffs for Massive MIMO Systems

Jabbar

2016

Applied Sciences

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“…4) Diversity Metric (Step 4 in Fig. 2): Diversity metric D(R) is used for quantifying the available diversity order for a given Rayleigh fading MIMO system with correlation matrix R. It is given by [39]:…”

Section: Simulation Frameworkmentioning

confidence: 99%

“…The metric varies between 1 and L, where L is the number of antennas used for achieving diversity. If D = 1, then there is no diversity gain and if D = L we obtain maximum diversity in the channel [39]. This metric allows us to compare different diversity systems based on their performance in a NLoS environment.…”

Section: Simulation Frameworkmentioning

confidence: 99%

Diversity Performance of Off-Body MB-OFDM UWB-MIMO

Marinova

Thielens

Tanghe

et al. 2015

IEEE Trans. Antennas Propagat.

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Abstract-This paper introduces a novel formalism to improve the performance of an off-body system by deploying multiple Ultra Wide Band (UWB) antennas, positioned strategically on the body. A methodology is presented for determining the optimal positions of UWB antennas on the body, necessary to provide a reliable Mult-Band Orthogonal Frequency Division Multiplexing (MB-OFDM) UWB diversity antenna system operating in the Federal Communications Commission frequency band between 3.1 and 10.6 GHz. By evaluating the diversity metric, using simulation and measurement data, it is shown that the performance of such a system is stable throughout the entire investigated frequency band for both indoor and outdoor environments. There is a good agreement between the simulated and measured diversity values with a deviation of less than 9%. Therefore, the proposed technique optimizes the antennas' positions for maximum diversity performance within a very broad frequency band, independent of the used wireless communication standard. Thus, the obtained diversity system might be used in any kind of wireless communication link within that frequency band, e.g. UWB-OFDM, UWB MB-OFDM, UWB or even narrowband transmission.

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“…Ivrlac and Nossek introduced the "Diversity Measure" [4] to characterise the fading on multi-antenna systems, effectively a scalar indicating the evenness of the distribution of eigen values of the correlation matrix.…”

Section: Diversity Measurementioning

confidence: 99%

Testing for Kronecker separability in measured channels

Kotterman¹,

Thomä²

2007

2nd European Conference on Antennas and Propagation (EuCAP 2007)

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Kronecker-separable MIMO channels, especially for larger MIMO configurations, are found more often in system simulations than in reality and some good physical explanations for the latter are available. This paper treats testing Kronecker-separability from a statistical perspective. The point raised is that for larger configurations the dimensions of the full correlation matrix become too large (equal to [NM×NM], with N number of receivers and M number of transmitters) for reliable estimation with the limited number of realisations normally available. Some examples are given, based on synthetic and measured data.

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Quantifying diversity and correlation in Rayleigh fading MIMO communication systems

Cited by 33 publications

References 4 publications

Analysis and Evaluation of Performance Gains and Tradeoffs for Massive MIMO Systems

Analysis and Evaluation of Performance Gains and Tradeoffs for Massive MIMO Systems

Diversity Performance of Off-Body MB-OFDM UWB-MIMO

Testing for Kronecker separability in measured channels

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