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The combination of distributed antenna systems (DAS) and multiple input multiple output (MIMO) schemes opens the way to a variety of coverage solutions for indoor environment. In this paper

MIMO transmission techniques are necessary for present and future indoor mobile radio systems to achieve a spectral efficiency of 30 bit/s/Hz, as required by the long term evolution-advanced (LTE-A) standard [

Differently from what happens outdoors, a large number of easily accessible fixed-terminal locations are available indoors due to the intrinsically 3-dimensional topology and to the presence of cable raceways, double ceilings, and so forth. Therefore distributed antenna systems (DAS) indoor coverage-extension schemes can be implemented where the same signal (of a single base station) is distributed to a number of remote antenna units (RAUs) using copper cables or optical fibers (F-DAS) to achieve a better radio coverage [

The traditional MIMO implementation over a DAS scheme requires providing each RAU with all

Recent studies have shown the advantages of adopting “

Of course in large indoor environments with many RAU locations multiple repetitions of the

Interleaved-MIMO DAS schemes are being considered with great interest by operators and installers because they might yield a performance level comparable to that of a colocated MIMO DAS (

For these reasons, the i-MIMO DAS concept is further investigated and discussed for higher-order MIMO schemes in the present paper, where LTE-advanced link-level simulations (Section

In order to provide planning guidelines, a single benchmark system standard (LTE-advanced) has been considered and the problem has been simplified by taking into account only major parameters such as the signal-to-noise ratio (SNR) and the PI that depend on the particular i-MIMO DAS deployment. Other factors such as the multipath richness and other propagation characteristics can have an important impact on performance, but they cannot be engineered as they primarily depend on the propagation environment and therefore their role has not been deeply analyzed here. In the following we will simply assume the multipath richness to be large enough not to represent a limit to MIMO performance.

The application of the MIMO concept to distributed antenna systems is analyzed here with particular reference to the spatial multiplexing capability, although other transmission techniques such as

The present work considers the implementation of i-MIMO DAS in large indoor environments with

In case a linear layout is required and/or low-order i-MIMO schemes are considered, the best spatial deployment for the different MIMO branches can be often handled on the base of somehow evident, intuitive considerations [

In a 2D/3D coverage case and for high-order MIMO however the best deployment scheme may be no longer trivial, as some different, interleaved solutions might exist and should be therefore evaluated.

In order to limit the spatial PI it is intuitive that the different MIMO branches should be somehow arranged in square/rectangular “clusters” (Figure

Uniform, 2D

Intuitively, the 2-shift solution should lead to a more uniform branch-signal distribution; however, actual performance must be assessed by simulation as shown in Section

In conclusion, irrespective of the i-MIMO order, the concept of “

In order to effectively set up the system level simulations described in the next subsection some major parameters of the i-MIMO DAS channel have been preliminarily investigated through an extensive measurement campaign carried out in a typical modern indoor office, where up to 4 RAUs have been considered and several measurement routes have been deployed in different rooms and along a corridor. All measurements have been performed in static conditions at the frequency of 858 MHz for a 2 × 2 i-MIMO arrangement. In order to get rid of the local multipath effects, the measured data have been collected several times moving the receiving array over a spatial grid centered on each measurement position. Further details about the measurement campaign can be found in [

The overall amount of gathered experimental data has been postprocessed to achieve the statistics of both the channel correlations and the power imbalance. In particular, Figure

CDF of the magnitude of the correlation coefficients extracted from the measurements.

All the CDFs appear rather similar, with median values always between 0.2 and 0.25 and correlation values seldom larger than 0.4. Such results clearly support the assumption—made at the end of the introduction—that multipath richness should not represent a limit to the performance of an i-MIMO system, which is therefore mainly affected by path-loss and shadowing, which practically determine the value of both the PI and the SNR.

The experimental CDF of the power imbalance is shown in Figure

Experimental CDF of the PI in the considered scenarios.

As described in the next subsection, in order to effectively assess the performance of i-MIMO DAS systems, the statistics shown in Figures

A wireless system must be able to cope with high downlink PI in order to achieve good performance in i-MIMO DAS configuration. For MIMO systems of order higher than

As a benchmark to study i-MIMO performance and planning strategies in real-life cases, the LTE-advanced standard is considered in the present work [

For each realization, the channel matrices have been randomly generated according to the full-correlation model (see [

Then, random imbalances between the MIMO branches have been also introduced, according to the PI statistics shown in Figure

The final outcome of the simulations is the downlink channel-throughput as a function of

Downlink throughput values provided by the LTE-A link-level simulator for the

Downlink throughput values provided by the LTE-A link-level simulator for the

Figures

It is worth noticing that the throughput plot versus SNR and

The results for high-order i-MIMO DAS arrangements provide manifold confirmations of the outcomes of the analysis already carried out in [

different “throughput zones,” that is, portions of the (SNR,

the throughput values seem to increase with SNR and on the contrary decrease for increasing power imbalance;

the full-throughput achievable within the

since the simulated throughput values corresponding to different channel realizations having the same

With regard to the planning guidelines of Section

It is worth noticing that also multiuser MIMO is included in the LTE-A standard where different branches in an i-MIMO scheme would be used to serve different users. Although the i-MIMO concept and the methodological approach of this work are still valid, the PI and thus the

In this section, considerations and guidelines for the planning and the deployment of i-MIMO DAS systems in reference, regular 1D (corridor), 2D (single floor), and 3D (multifloor) layouts are provided on the base of both the throughput plots of Section

In [

Given a propagation environment, that is, specific-attenuation

There is therefore affinity between i-MIMO DAS planning and traditional cellular planning, where radio coverage must be provided in the first step and then the cluster-size must be chosen so as to satisfy signal-to-interference (SIR) requirements. Here the MIMO order

Since planning step

On the contrary, planning step

It is worth noticing that hereafter the performance of the i-MIMO solutions will not be evaluated in terms of absolute throughput, but rather in terms of “average (relative) gain with respect to the SISO case” (

According to this definition,

In general, if

It is therefore very important to choose the appropriate MIMO order

If

In summary the present section provides the following useful results:

different i-MIMO DAS deployment solutions are evaluated to identify the best one, especially in 2D and 3D cases where different, apparently equivalent solutions are possible, as highlighted in Section

for each reference case, the equivalent number of useful branches is determined as a function of RAU

If a linear deployment is considered (e.g., RAUs positioned along a corridor) and assuming that the receiver moves along a route parallel to the corridor where the RAUs are located, both SNR and

This behavior is clearly confirmed by the example in Figure

Behaviour of

It is evident that the better the SNR, the worse the PI and vice versa; therefore, the system design (i.e., the RAUs’ spatial deployment and the choice of the MIMO order) should aim at properly balancing coverage (SNR) and imbalance (

Figure

Comparison of 2-, 4-, and 8-branch i-MIMO DAS performance in the linear deployment (corridor) case. Average number of branches under threshold (

It is worth noticing that the larger the MIMO order, the higher the performance sensitivity to the propagation conditions. In fact,

Low

The combined effects of SNR and

Performance of

Performance of

In both cases, the best performance (i.e., the highest

Two different values of

The effectiveness of the interleaved approach is evaluated in Figure

Performance comparison of different 8-branch i-MIMO 2D deployments (no-shift, 1-shift, and 2-shift). Average number of branches under threshold (

The benefit provided by a shifted deployment is slight if

A performance comparison for different MIMO order values is presented in Figures

Comparison of 2-, 4-, 8-branch i-MIMO DAS average performance in the 2D deployment case. Average number of branches under threshold (

Comparison of 2-, 4-, and 8-branch i-MIMO DAS performance (% of area where more than 75% of maximum throughput is achieved) in the 2D deployment case, for different values of the propagation model parameters (RAU antenna distance: 20 m).

Similarly to the 1D case, Figure

The 4-branch case represents an intermediate case, but more specifically it shows a more marked similarity to the 2-branch solution, since the RAU transmitted power required to reach the full MIMO throughput (

For the sake of brevity, the analyses of the 3D case are here limited to the solution represented in Figure

3D

The 2 × 2 square cluster is repeated over each floor according to the no-shift coverage solution shown in Figure

Moreover, an additional floor penetration loss of 10 dB is considered for the evaluation of the intensity of the signals received from RAUs placed on different floors with respect to the receiver.

System performance is represented in Figure

Performance comparison of

On the contrary, if

Planning strategies for interleaved-MIMO DAS indoor coverage-extension solutions are studied in the present paper. Although LTE-A standard is adopted as a benchmark here, the proposed methodology, which is based on large-scale propagation parameters such as SNR and power imbalance (PI, measured through

Results show that proper, interleaved deployment solutions based on the concept of “cluster” should be adopted to keep PI low enough. In some 2D and 3D deployment cases a cluster-shifting can help further performance optimization.

PI is shown to increase with both MIMO order

It is wrong to adopt, say, a costly

Therefore, useful planning guidelines are proposed and graphs are derived to help the i-MIMO system designer determine the maximum MIMO order for which performance is not yet limited by power imbalance and therefore the best i-MIMO solution for given traffic and propagation conditions.

The authors declare that there is no conflict of interests regarding the publication of this paper.

This work has been carried out in the framework of and partly funded by the EU Project Architectures for Flexible Photonic Home and Access Networks (ALPHA), ICT CP-IP 212 352. This work has also been partly funded by the European Network of Excellence NEWCOM++. The authors thank their graduate student Stefano Fiaschi for the great help in carrying out system simulations.