Exact capacity distributions for MIMO systems with small numbers of antennas

Smith, Peter J.; Garth, L.M.; Loyka, Sergey

doi:10.1109/lcomm.2003.817318

Cited by 53 publications

(46 citation statements)

References 14 publications

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“…The "analytic variance (high SNR)" dashed lines are based on (24) for the 2 23 case, (31) for the 1 22 case, and (33) for the 1 2 1 case. The "analytic variance (exact)" curves are based on (9) for the 2 2 3 case, (20) for the 1 2 2 case, and (22) for the 1 2 1 case.…”

Section: Corollarymentioning

confidence: 99%

“…This is an important capacity measure for systems with stringent delay constraints, and it also provides information about the system diversity [19]. With the exception of the exact two/three antenna results presented in [20] and [21], outage capacity analysis has typically involved approximating the distribution of the mutual information, since exact closed-form solutions are not forthcoming. It has been shown that the Gaussian distribution provides a good approximation in many cases [5], [8], [13], [22], [23].…”

Section: Introductionmentioning

confidence: 99%

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On the Mutual Information Distribution of OFDM-Based Spatial Multiplexing: Exact Variance and Outage Approximation

McKay

Smith

Suraweera

et al. 2008

IEEE Trans. Inform. Theory

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Section: Corollarymentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

On the Mutual Information Distribution of OFDM-Based Spatial Multiplexing: Exact Variance and Outage Approximation

McKay

Smith

Suraweera

et al. 2008

IEEE Trans. Inform. Theory

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“…In (15), H(t) represents the random complex channel gain described using any suitable stochastic channel model. In this article, we have represented the random channel H(t) by a Suzuki process η(t).…”

Section: Statistical Properties Of the Capacity Of Suzuki Channelsmentioning

confidence: 99%

“…The Suzuki process is generated by taking the product of a Rayleigh and a lognormal process [14]. The analysis of the PDF, CDF, LCR, and ADF of the channel capacity of fast fading channels, like Rayleigh channels can be found, e.g., in [2][3][4], [15], [16]. However, there is a lack of information regarding the combined effects of shadowing and fast fading on the channel capacity.…”

Section: Introductionmentioning

confidence: 99%

A Study of the Influence of Shadowing on the Statistical Properties of the Capacity of Mobile Radio Channels

Rafiq

Pätzold

2008

Wireless Pers Commun

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Abstract. This paper 1 studies the influence of shadowing on the statistical properties of the channel capacity. The problem is addressed by using a Suzuki process as an appropriate statistical channel model for land mobile terrestrial channels. Using this model, exact solutions for the probability density function (PDF), cumulative distribution function (CDF), level-crossing rate (LCR), and average duration of fades (ADF) of the channel capacity are derived. The results are studied for different levels of shadowing, corresponding to different terrestrial environments. It is observed that the shadowing effect has a significant influence on the variance and the maximum value of the PDF and LCR of the channel capacity, but it has almost no impact on the mean capacity of the channel. The correctness of the theoretical results is confirmed by simulation using a stochastic channel simulator based on the sum-of-sinusoids principle.

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“…In [13], we considered the 'semi-correlated' Rayleigh channel model, where the transceiver end that only has m antennas experiences spatial correlation. For example, if n R n T and the receiving antennas are spatially correlated, then the columns of H are i.i.d., each with covariance matrix Q c .…”

Section: Semi-correlated Rayleigh Channelmentioning

confidence: 99%

Performance analysis of multiple-input multiple-output singular value decomposition transceivers during fading and other cell interference

Smith

Garth

Shafi³

2007

IET Microw. Antennas Propag.

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A generalised method is derived to compute the error probabilities of singular value decomposition (SVD)-based receivers for a multiple-input multiple-output (MIMO) system with uncoded transmission. The method can be used for a wide class of flat fading environments, including independent and identically distributed (i.i.d.) and semi-correlated Rayleigh and i.i.d. Ricean channels. Although the method is applied to equal-power binary phase shift keying, it can easily be extended to higher-order M-ary phase shift keying (M-PSK) and M-ary quadrature amplitude modulation (M-QAM) signal constellations and adaptive 'water-filling' schemes. The error probability curves derived from closed-form formulas and simulations demonstrate very close agreement. The error performances of channel inversion, minimum mean square error and zero forcing receivers are compared with the SVD receiver for a single-user system. The impact of multiple users is considered by studying the performance of an adaptive MIMO SVD transmission scheme operating in a cellular environment. In particular, the effect of inter-cell interference on the performance of the scheme is quantified, modelling the interference as increased Gaussian noise. A number of cellular layouts are examined and the impact of the resulting singal-to-interference and noise ratio on the constellation sizes that can be supported, the BER and so on is considered. The primary metric used for our performance analysis is the error-free transmission rate, which is derived for our adaptive system. For the cellular scenarios considered, it can be found that the effect of interference is considerable and the performance of the adaptive MIMO SVD scheme is only marginally better than that provided by conventional diversity methods. IntroductionThe pioneering work of Telatar [1] and Foschini and Gans [2] has resulted in immense interest in multiple-input multiple-output (MIMO) systems. They offer the promise of large system capacities, and thus are being considered for fourth generation wireless systems. However, the majority of work in this area has focussed on single-user MIMO systems, and recent results [3] suggest that the promised rates may not be available in cellular systems. Hence, in this paper we study the performance of both fixed and adaptive MIMO singular value decomposition (SVD) transmission schemes in a cellular environment and make the following contributions: † We present a generalised method that can be used to derive the exact symbol-error probability of fixed SVD-based MIMO receivers using uncoded transmission. We demonstrate the method for independent and identically distributed (i.i.d.) and semi-correlated Rayleigh and i.i.d. Ricean channels. Our results provide new insights in understanding the error performance of MIMO systems. For example, when the number of antennas is increased from two to four at both the transmit and receive ends, although the ergodic capacity increases, the error performance degrades. Hence, we are able to quantify the tradeoff betw...

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Exact capacity distributions for MIMO systems with small numbers of antennas

Cited by 53 publications

References 14 publications

On the Mutual Information Distribution of OFDM-Based Spatial Multiplexing: Exact Variance and Outage Approximation

On the Mutual Information Distribution of OFDM-Based Spatial Multiplexing: Exact Variance and Outage Approximation

A Study of the Influence of Shadowing on the Statistical Properties of the Capacity of Mobile Radio Channels

Performance analysis of multiple-input multiple-output singular value decomposition transceivers during fading and other cell interference

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