Dmitry Chizhik

MIMO radar: an idea whose time has come

It has recently been shown that multiple-input multiple-output (MIMO) antenna systems have the potential to improve dramatically the performance of communication systems over single antenna systems. Unlike beamforming, which presumes a high correlation between signals either transmitted or received by an array, the MIMO concept exploits the independence between signals at the array elements. In conventional radar, target scintillations are regarded as a nuisance parameter that degrades radar performance. The novelty of MIMO radar is that it takes the opposite view; namely, it capitalizes on target scintillations to improve the radars performance. We introduce the MIMO concept for radar. The MIMO radar system under consideration consists of a transmit array with widely-spaced elements such that each views a different aspect of the target. The array at the receiver is a conventional array used for direction finding (DF). The system performance analysis is carried out in terms of the Cramer-Rao bound of the mean-square error in estimating the target direction. It is shown that MIMO radar leads to significant performance improvement in DF accuracy.

Evaluation of Transmit Diversity in MIMO-Radar Direction Finding

It has been recently shown that multiple-input multiple-output (MIMO) antenna systems have the potential to dramatically improve the performance of communication systems over single antenna systems. Unlike beamforming, which presumes a high correlation between signals either transmitted or received by an array, the MIMO concept exploits the independence between signals at the array elements. In conventional radar, the targets radar cross section (RCS) fluctuations are regarded as a nuisance parameter that degrades radar performance. The novelty of MIMO radar is that it provides measures to overcome those degradations or even utilizes the RCS fluctuations for new applications. This paper explores how transmit diversity can improve the direction finding performance of a radar utilizing an antenna array at the receiver. To harness diversity, the transmit antennas have to be widely separated, while for direction finding, the receive antennas have to be closely spaced. The analysis is carried out by evaluating several Cramer-Rao bounds for bearing estimation and the mean square error of the maximum likelihood estimate

Performance of MIMO radar systems: advantages of angular diversity

Inspired by recent advances in multiple-input multiple-output (MIMO) communications, this paper introduces the statistical MIMO radar concept. The fundamental difference between statistical MIMO and other radar array systems is that the latter seek to maximize the coherent processing gain, while statistical MIMO radar capitalizes on the diversity of target scattering to improve radar performance. Coherent processing is made possible by highly correlated signals at the receiver array, whereas in statistical MIMO radar, the signals received by the array elements are uncorrelated. It is well known that in conventional radar, slow fluctuations of the target radar cross-section (RCS) result in target fades that degrade radar performance. By spacing the antenna elements at the transmitter and at the receiver such that the target angular spread is manifested, the MIMO radar can exploit the spatial diversity of target scatterers opening the way to a variety of new techniques that can improve radar performance. In this paper, we focus on the application of the target spatial diversity to improve detection performance. The optimal detector in the Neyman-Pearson sense is developed and analyzed for the statistical MIMO radar. An optimal detector invariant to the signal and noise levels is also developed and analyzed. In this case as well, statistical MIMO radar provides great improvements over other types of array radars.

Analysis and performance of some basic space-time architectures

In this paper, we discuss some of the most basic architectural superstructures for wireless links with multiple antennas: M at the transmit site and N at the receive site. Toward leveraging the gains of the last half century of coding theory, we emphasize those structures that can be composed using spatially one dimensional coders and decoders. These structures are investigated primarily under a probability of outage constraint. The random matrix channel is assumed to hold steady for such a large number of M-dimensional vector symbol transmission times, that an infinite time horizon Shannon analysis provides useful insights. The resulting extraordinary capacities are contrasted for architectures that differ in the way that they manage self-interference in the presence of additive receiver noise. A universally optimal architecture with a diagonal space-time layering is treated, as is an architecture with horizontal space-time layering and an architecture with a single outer code. Some capacity asymptotes for large numbers of antennas are also included. Some results for frequency selective channels are presented: It is only necessary to feedback M rates, one per transmit antenna, to attain capacity. Also, capacity of an (M,N) link is, in a certain sense, invariant with respect to signaling format.

A Wideband Spatial Channel Model for System-Wide Simulations

A wideband space-time channel model is defined, which captures the multiple dependencies and variability in multicell system-wide operating environments. The model provides a unified treatment of spatial and temporal parameters, giving their statistical description and dependencies across a large geographical area for three outdoor environments pertinent to third-generation cellular system simulations. Parameter values are drawn from a broad base of recently published wideband and multiple-antenna measurements. A methodology is given to generate fast-fading coefficients between a base station and a mobile user based on the summation of directional plane waves derived from the statistics of the space-time parameters. Extensions to the baseline channel model, such as polarized antennas, are given to provide a greater variety of spatial environments. Despite its comprehensive nature, the models implementation complexity is reasonable so it can be used in simulating large-scale systems. Output statistics and capacities are used to illustrate the main characteristics of the model

Multiple input multiple output measurements and modeling in Manhattan

Narrowband MIMO measurements using 16 transmitters and 16 receivers at 2.11 GHz were carried out in Manhattan (see Ling, J. et al., IEE Electronics Letters, vol.37, no.16, p.1041-2, 2001). High capacities were found for full as well as smaller array configurations, all within 80% of the fully scattering channel capacity. Correlation model parameters are derived from the data. Spatial MIMO channel capacity statistics are found to be well represented by the separate transmitter and receiver correlation matrices, with a median relative error in capacity of 3%, in contrast with the 18% median relative error observed by assuming uncorrelated antennas. A reduced parameter model (4 parameters) has been developed to represent the channel correlation matrices statistically. These correlation matrices are used to generate H matrices with capacities that are consistent within a few percent of those measured in New York. Our spatial channel model allows simulations of H matrices for arbitrary antenna configurations. These channel matrices may be used to test receiver algorithms in system performance studies. These results may also be used for antenna array design, as the decay of mobile antenna correlation with antenna separation is reported. An important finding for the base transmitter array was that the antennas were largely uncorrelated even at antenna separations as small as two wavelengths.

A generalized space-time multiple-input multiple-output (MIMO) channel model

This paper presents a generalized multiple-input multiple-output (MIMO) channel modeling technique for link level and system level simulations. The model combines the correlation approach and wave superposition approach to achieve both accuracy and efficiency. The spatial, temporal, and frequency dispersions of the MIMO channels are implicitly modeled based on any given statistics. Polarizations, channel transitions, uplink and downlink channels, and keyhole-pinhole channels are modeled as optional modules. Theoretical justifications as well as experimental verification of the model are also presented. The proposed model can be applied to system simulations for MIMO as well as other adaptive antenna applications.

Lateral, full-3D and vertical plane propagation in microcells and small cells

When the height of the transmitter is close to building heights, over-rooftop contributions, i.e. full-3D rays or rays in the vertical plane, become relevant in propagation. Full-3D propagation, vertical plane propagation and lateral propagation are compared, both mutually and against measurements in Munich (Germany) and Rosslyn (VA, USA). To perform our study we made use of a full-3D ray tracing tool. In addition, a deterministic vertical plane prediction model was implemented based on a literature review of published models. In Munich, which has a regular mixture of building heights with virtually no high rise buildings, our deterministic vertical plane model was found to be accurate in predicting the average measured power for receivers far from the transmitter. Deterministic models require, in general, less calibration with measurements than empirical models. The wedge representation of buildings in the vertical plane was found to give better agreement with measurements than the classical knife-edge representation.

Evolution of Base Stations in Cellular Networks: Denser Deployment versus Coordination

It has been demonstrated that base station cooperation can reduce co-channel interference (CCI) and increase cellular system capacity. In this work we consider another approach by dividing the system into microcells through denser base station deployment. We adopt the criterion to maximize the minimum spectral efficiency of served users with a certain user outage constraint. In a two-dimensional hexagon array with homogeneous microcell structure, under the proposed propagation model denser base station deployment outperforms suboptimal cooperation schemes (zero-forcing) when the density increases beyond 3 - 12 base stations per km2, the exact value depending on the rules of outage user selection. However, close- to-optimal cooperation schemes (zero-forcing with dirty-paper- coding) are always superior to denser deployment. Performance of a hierarchial cellular structure mixed with both macrocells and microcells is also evaluated.

Spatial and temporal variations of MIMO channels and impacts on capacity

This paper presents analysis for spatial and temporal variations of multiple-input-multiple-output (MIMO) channels at the mobile. The channel study is based on the narrowband measurements at 2.11 GHz in Manhattan, New York with 16 transmitting antennas and 16 receiving antennas. Doppler spread and angle of arrival (AOA) are derived from the temporal correlation of field components. The results show that the AOA at the mobile is not uniformly distributed. The restricted AOA distribution results in approximately twice the correlation distance and correlation time than the predicted values from the Jakes (1974) model. The measured median coherence time is at least a few seconds for stationary channels, and 90 ms at a mobile pedestrian speed of 3 km/hr. These observations hold for both vertically and horizontally polarized antennas. The measured median RMS angular spread at the mobile is 22.5/spl deg/ for horizontally polarized antennas and 25.5/spl deg/ for vertically polarized antennas.