Deep brain stimulation (DBS) is a targeted manipulation of brain circuitry to treat neurological and neuropsychiatric conditions. Optimal DBS lead placement is essential for treatment efficacy. Current targeting practice is based on preoperative and intraoperative brain imaging, intraoperative electrophysiology, and stimulation mapping. Electrophysiological mapping using extracellular microelectrode recordings aids in identifying functional subdomains, anatomical boundaries, and disease-correlated physiology. The shape of single-unit action potentials may differ due to different biophysical properties between cell-types and brain regions. Here, we describe a technique to parameterize the structure and duration of sorted spike units using a novel algorithmic approach based on canonical response parameterization, and illustrate how it may be used on DBS microelectrode recordings. Isolated spike shapes are parameterized then compared using a spike similarity metric and grouped by hierarchical clustering. When spike morphology is associated with anatomy, we find regional clustering in the human globus pallidus. This method is widely applicable for spike removal and single-unit characterization and could be integrated into intraoperative array-based technologies to enhance targeting and clinical outcomes in DBS lead placement.

Keys for symmetric encryption can be established by generating key bits from the mutually-observed randomness present within estimates of a reciprocal wireless channel. We consider this approach for key establishment in multiple-input multiple-output (MIMO) systems and provide a channel estimation strategy that increases the key rate, or the mutual information between the channel estimates at the two nodes. The technique applies MIMO transmit and receive beamformers derived from the eigenvectors of the covariance matrix and then iteratively optimizes the power allocated to each transmit beamformer. Simulation results demonstrate the iterative behavior and the achieved performance of the proposed algorithm.

When establishing secret encryption keys using estimates of the reciprocal wireless channel, the number of key bits that can be generated for a static or slowly varying propagation environment can be enhanced by randomly changing the radiation properties of a reconfigurable antenna. However, prior studies of this approach have been limited and have not considered a high degree of antenna reconfigurability. This paper uses simulations and experimental measurements to characterize the impact of reconfigurable antenna complexity on the performance of key establishment in different static propagation environments and in the presence of a multi-antenna eavesdropper. The results demonstrate that reconfigurable antennas can significantly enhance the security, even when the eavesdropper antennas are adjacent to or surround one of the legitimate nodes. The results further demonstrate that increasing the number of reconfigurable parasitic elements notably increases the achieved performance.

Establishing secret keys from the commonly-observed randomness of reciprocal wireless propagation channels has recently received considerable attention. We consider such key establishment between two multiantenna nodes that use beamforming for communication, showing that the upper bound on the number of key bits that can be generated from the channel observations can be maximized by properly probing the channel. Specifically, we demonstrate that the eigenvectors of the channel spatial covariance matrix should be used as beamformer weights during channel estimation and we optimize the energy allocated to channel estimation for each beamformer weight under a total energy constraint. Finally, by assuming that the channel covariance is separable, we illustrate implementation of the technique for practical beamforming systems and more advanced signal models that incorporate antenna mutual coupling.

The performance of techniques for establishing secret encryption keys from the reciprocal electromagnetic propagation between two wireless radios is generally measured by comparing the number of key bits generated to the key rate, or the information theoretic bound on the number of key bits that can be determined for a single independent channel estimate. While typically this bound is computed by assuming that the radios have no information regarding the channel, recent work has demonstrated an approach for computing this bound for nodes using beamformed antenna arrays that know the spatial covariance of a wide-sense stationary channel. Since this bound does not directly indicate how to perform practical channel estimation to obtain estimates that can achieve the bound, the prior work demonstrates an approximation that indicates a practical channel estimation procedure while yielding a mutual information near that of the key rate in rich multipath fading environments. This paper demonstrates appreciable degradation in the mutual information achieved using this approximation when the channel includes a line-of-sight component and proposes a modified approximation technique that performs well over a broad range of propagation conditions.

Authenticating wireless devices based on features of their transmitted waveform has become a topic of considerable interest. Recent work in this arena has shown that examination of features in a modulated waveform can lead to highly precise identification of 802.11 devices. This paper experimentally demonstrates improved identification accuracy and reduced sensitivity to identification parameters when such techniques are applied to the multiple transmitters within multiple-input multiple-output devices. It further studies an information theoretic technique for determining which radiometric features are most effective in discriminating devices and analyzes the identification performance as a function of the number of features used. Finally, because some radiometric features are sensitive to environmental conditions and, therefore, drift with time, the analysis explores the impact of radiometric feature drift both on feature prioritization and on identification performance.

When implementing data encryption and decryption in a symmetric cryptosystem, secure distribution of the secret key to legitimate nodes can be a challenge. In this paper, we consider establishing secret keys using the common wireless channel, with particular emphasis on the spatial and temporal correlations of the channel coefficients. Specifically, we investigate the influence of channel correlation on the bound of the key size generated from the common channel using a simple single-input single-output channel model, and we verify the existence of a sampling approach able to generate a key using the minimum possible sampling window. We also explore decorrelation of the channel coefficients in a multiple-input multiple-output channel, and we use a statistical independence test to demonstrate that this process cannot be separated into spatial and temporal decorrelation processes. The insights gained from these studies assist in the development of a practical key generation protocol based on a published channel coefficient quantization method and incorporating flexible quantization levels, transmission of the correlation eigenvector matrix, and LDPC coding to improve key agreement in an authenticated public channel. Finally, we present simulations with real channel measurements that solidify the fundamental conclusions.

In an ad hoc network, efficiently scheduling the optimal multi-user multiple-input multiple-output links is challenging. Specifically, optimal scheduling requires full understanding of the subspace structure of the channel matrices, but exploiting this detailed information during scheduling requires significant computational and algorithmic complexity. This paper demonstrates efficient yet effective scheduling based on link signal-to-noise ratio coupled with the average ratio of the maximum to minimum channel singular values and the channel Doppler frequency. Computational results show that this scheduling technique is able to achieve average network sum rates that approach those of the optimal link topology.

This paper proposes a practical protocol useful for establishing encryption keys between nodes in a wireless network. The method is designed to enable creation of long keys by extracting the increased randomness inherent in reciprocal time-variant multiple-input multiple-output wireless channels. The presentation provides a strategy for exploiting the degrees of freedom existing in the protocol to decorrelate the information in the public discussion from the key information as well as the channel state information. The paper further discusses several error reduction techniques that can efficiently enhance key agreement between the multiple-antenna nodes. Simulations based on a realistic time-variant channel model demonstrate the efficiency of the key establishment as well as the probability of key agreement for the protocol.

This paper proposes an architecture for using multiple-input multiple-output techniques for a multimode fiber broadcast channel, allowing simultaneous transmission of unique streams to different users on the same fiber while using square-law detection. The resulting system throughput scales nearly linearly with the number of transmitters and receivers. The paper also proposes a training scheme appropriate for use with square-law detection.

Linear precoding (beamforming) techniques exist that maximize the sum rate in multi-antenna broadcast channels. Such algorithms require accurate channel state information (CSI) at the transmitter and are performance sensitive to erroneous or outdated CSI. The current work focuses on adapting these algorithms to work on the statistics of the channel, rather than channel state, in order to provide more stable performance. This stable beamforming method is shown to require the full spatial correlation matrix thus suffering from high complexity in the feedback channel. Parameterization of the spatial correlation using popular channel models is also considered to make the proposed beamforming practical.

Traditional non-linear (dirty paper coding) and linear (beamforming) preceding techniques that maximize the sum rate in the multi-antenna broadcast channel often suffer severe performance degradation when the channel state information (CSI) at the transmitter is erroneous or outdated. This has motivated the recent development of a linear preceding algorithm that uses the channel distribution information (CDI) rather than channel state to provide more stable performance in time-varying environments. This paper extends the prior analysis by using simulations with measured multi-user multi-antenna broadband channel responses to examine the effect of frequency selective channel characteristics on the behavior of the traditional CSI- based strategies as well as the more recent CDI-based approach. The results show that the CDI-based beamformer can offer superior performance with reduced feedback communication requirements.

This work explores the performance of a multiple-input multiple-output broadcast channel where both the transmitter and receivers have outdated channel knowledge due to node motion or other time-variations in the communication channel. A performance analysis based on measured channel responses reveals significant throughput degradation for optimal linear and nonlinear precoding strategies unless the channel state information (CSI) is frequently fed back to the transmitter. The paper then develops a linear beamforming precoding strategy based on channel distribution information in the form of a full spatial correlation matrix for each user. This algorithm is shown to provide highly stable communication, with a throughput that is higher than that for optimal precoders operating on outdated CSI, in a time-variant environment, indicating that this approach can operate with significantly reduced feedback frequency. Furthermore, the paper demonstrates the use of the well-known Kronecker and Weichselberger models to parameterize the full correlation matrix to enable further reduction in the amount of feedback data required for implementation of the new beamforming technique.

Previous results for correlated block-fading MIMO channels with covariance information indicate guaranteed capacity growth with additional transmit elements and that in rapidly fading channels, vanishing element spacing maximizes capacity. However, because prior analysis neglects antenna electromagnetic coupling, the observations are not necessarily valid for small inter-element spacing. This work applies radiated power considerations to the analysis to demonstrate that additional elements do not always increase capacity and that vanishing element spacing is not optimal. An effective gain metric is introduced that quantifies the performance increase with additional transmitters in the presence of transmit correlation and mutual coupling. Performance simulations using the electromagnetic properties of uniform linear arrays characterized by closed form expressions for Hertzian dipoles and detailed finite-difference time-domain (FDTD) simulations of half-wave dipoles illustrate that capacity gains arc possible when correlation stems from directional bias in the channel but not when it arises due to compact element spacing.

Multiple-input multiple-output (MIMO) communication systems can theoretically use array superdirectivity to optimally exploit the propagation channel. This superdirectivity leads to very large capacity bounds, particularly when the antennas are closely spaced. However, because superdirective behavior is difficult to achieve in practice, new capacity bounds have been formulated for the case where the level of array superdirectivity is constrained. Existing capacity analyses limit the superdirectivity in a suboptimal way. In this paper, the impact of superdirectivity in the capacity solution is limited by introducing finite ohmic loss in the transmit and receive antenna elements. Computational results reveal that even a small amount of ohmic loss significantly decreases the achievable system capacity

A recent study on correlated block-fading MIMO channels with transmit covariance information indicates guaranteed capacity growth with additional transmit elements, in contrast to previous results for uncorrelated channels. Also, for very rapidly fading channels, the results indicate the optimality of placing antenna elements as close together as possible. In this work, application of radiated power considerations indicates that transmit beamforming only increases capacity when this gain results from correlation inherent in the channel, not correlation that is simply offset by increased antenna coupling. The new analysis reveals that when multipath is directionally biased, antenna spacings of 0.3 to 0.6 wavelengths are optimal, and that when no such bias is present, antennas should be placed as far apart as possible. As expected, the electromagnetic analysis shows that at zero element separation, the array yields no capacity gain over a single antenna.

A cost-effective, experimental MIMO channel sounder is presented, capable of performing measurements with up to eight transmit and eight receive elements over 80 MHz of system bandwidth. The system provides the wideband channel transfer matrix for both indoor and outdoor wireless communication scenarios, allowing direct measurement of key MIMO system parameters. The system is described, fundamental hardware building blocks are outlined, and post-processing data algorithms are presented. Initial investigations on the effect of frequency scaling and array configuration at 5.2 GHz and 2.4 GHz are also presented.

In antenna diversity systems, mutual coupling of closely-spaced antennas alters the element radiation and impedance properties, thereby impacting the system diversity performance. Past studies have emphasized the effect of the distorted pattern and largely neglected the effect of altered impedance (and therefore receive signal-to-noise ratio) on the diversity behavior. Here, we present a new network analysis which facilitates a complete characterization of the system and comparison of diversity performance for various impedance terminations. Representative results reveal that for closely-spaced antennas, the termination can play a noticeable role in determining the diversity gain offered by coupled antennas.

A diffuse spectrum estimation method is presented that is suitable for direction finding for channels with diffuse electromagnetic scattering. The diffuse channel may be the result of physical phenomena (e.g., rough-surface scattering) or limited angular and temporal discrimination of the channel probing equipment. The method decomposes the ideal noncoherent spectrum into a sum of power-weighted basis functions. The basis function coefficients are obtained through a linear programming solution. The method is applied to recent radio channel data collected on the Vienna University of Technology campus. Parameters for a path-based model are extracted using the technique. Site-specific spectra and global capacity comparisons indicate the utility of this new method.

This paper provides an analytical framework useful for assessing the use of all six electric and magnetic electromagnetic field polarizations for multiantenna communications systems. The approach uses a mapping between the induced signal currents and the received electromagnetic field in order to formulate a diversity interpretation of the six-polarization problem. Application of the framework to a simple, yet representative, channel model demonstrates that for full multipath elevation and azimuthal angle spread, six communication modes are theoretically possible. However, to implement the system requires more antenna design work since a straightforward implementation is found to reduce the potential number of modes to three.

A new framework for the analysis of multiple-input multiple-output (MIMO) wireless systems is introduced to account for mutual coupling effects in the antenna arrays. The multiport interactions at transmit and receive are characterized by representing the channel using a scattering parameter matrix. A new power constraint that limits the average radiated power is also introduced. The capacity of the MIMO system with mutual coupling is defined as the maximum mutual information of the transmit and receive vectors over all possible transmit signaling and receive loading. Full-wave electromagnetic antenna simulations combined with a simple path-based channel model are used to demonstrate the utility of the method.

Detailed performance assessment of space-time coding algorithms in realistic channels is critically dependent upon accurate knowledge of the wireless channel spatial characteristics. This paper presents an experimental measurement platform capable of providing the narrowband channel transfer matrix for wireless communications scenarios. The system is used to directly measure key multiple-input-multiple-output parameters in an indoor environment at 2.45 GHz. Linear antenna arrays of different sizes and construction with up to ten elements at transmit and receive are utilized in the measurement campaign. This data is analyzed to reveal channel properties such as transfer matrix element statistical distributions and temporal and spatial correlation. Additionally, the impact of parameters such as antenna element polarization, directivity, and array size on channel capacity are highlighted. The paper concludes with a discussion of the relationship between multipath richness and path loss, as well as their joint role in determining channel capacity.

Principal component analysis (PCA) has previously been used to characterize snowmelt on the Greenland ice sheet using all seven SSM/I channels. Three extensions to this algorithm are presented in this work. First, a location dependent thresholding technique is developed that facilitates improved sensitivity in snowmelt detection as compared to prior studies. Second, an adapted PCA algorithm is formulated that is able to link key physical processes with vectors in the SSM/I data eigenspace. Finally, the inclusion of active scatterometer data in the PCA implementation is shown to offer additional information that assists in snowmelt estimation.

Detailed performance assessment of space-time coding algorithms in realistic channels is critically dependent upon accurate knowledge of the wireless channel spatial characteristics. This paper presents an experimental measurement platform capable of providing the channel transfer matrix for indoor and outdoor wireless communications scenarios. The system allows direct measurement of key multiple input multiple output parameters for 16 transmit and 16 receive antennas. The basic hardware blocks are outlined, and the data post-processing algorithms are presented. Representative data showing, channel capacity and spatial correlation for several indoor sites are provided.

This paper presents measured data from a narrowband multiple-input multiple-output (MIMO) channel probe in an indoor office/laboratory environment. The system employs ten transmit and ten receive antennas and computes the 10 /spl times/ 10 narrowband channel matrix at 2.45 GHz every 80 milliseconds. We use the data to study the statistical behavior of the channel coefficients and the resulting channel capacity. We also demonstrate the ability of a simple statistically based physical model to accurately represent the channel behavior. The results of this model are compared to more conventional models that assume complex normal distributions of the channel matrix elements.

This paper presents results from an experimental platform designed to measure the transfer matrix for indoor and outdoor multiple-input multiple-output (MIMO) channels with up to 16 transmit and receive antenna elements. Key aspects of the hardware system and data post-processing techniques are provided. A variety of measurements have been taken with the platform at 2.45 GHz in a typical indoor environment. The collected data have been processed to highlight a variety of channel features, including the statistical distributions of the channel matrix elements and the inherent capacity of the wireless MIMO channel for different numbers of antenna elements, polarizations, and element directivities.

Most previously proposed statistical models for the indoor multipath channel include only time of arrival characteristics. However, in order to use statistical models in simulating or analyzing the performance of systems employing spatial diversity combining, information about angle of arrival statistics is also required. Ideally, it would be desirable to characterize the full spare-time nature of the channel. In this paper, a system is described that was used to collect simultaneous time and angle of arrival data at 7 GHz. Data processing methods are outlined, and results obtained from data taken in two different buildings are presented. Based on the results, a model is proposed that employs the clustered "double Poisson" time-of-arrival model proposed by Saleh and Valenzuela (1987). The observed angular distribution is also clustered with uniformly distributed clusters and arrivals within clusters that have a Laplacian distribution.

In personal communications, the electromagnetic interaction between handset-mounted antennas and the nearby biological tissue is a key consideration. This paper presents a thorough investigation of this antenna-tissue interaction using the finite-difference time-domain (FDTD) electromagnetic simulation approach with detailed models of real-life antennas on a transceiver handset. The monopole, side-mounted planar inverted F, top-mounted bent inverted F, and back-mounted planar inverted F antennas are selected as representative examples of external and internal configurations. Detailed models of the human head and hand are implemented to investigate the effects of the tissue location and physical model on the antenna performance. Experimental results are provided which support the computationally obtained conclusions. The specific absorption rate (SAR) in the tissue is examined for several different antenna/handset configurations. It is found that for a head-handset separation of 2 cm, the SAR in the head has a peak value between 0.9 and 3.8 mW/g and an average value between 0.06 and 0.10 mW/g for 1 W of power delivered to the antenna. Additionally, the head and hand absorb between 48 and 68% of the power delivered to the antenna.>