James V. Krogmeier

Millimeter Wave Beamforming for Wireless Backhaul and Access in Small Cell Networks

Recently, there has been considerable interest in new tiered network cellular architectures, which would likely use many more cell sites than found today. Two major challenges will be i) providing backhaul to all of these cells and ii) finding efficient techniques to leverage higher frequency bands for mobile access and backhaul. This paper proposes the use of outdoor millimeter wave communications for backhaul networking between cells and mobile access within a cell. To overcome the outdoor impairments found in millimeter wave propagation, this paper studies beamforming using large arrays. However, such systems will require narrow beams, increasing sensitivity to movement caused by pole sway and other environmental concerns. To overcome this, we propose an efficient beam alignment technique using adaptive subspace sampling and hierarchical beam codebooks. A wind sway analysis is presented to establish a notion of beam coherence time. This highlights a previously unexplored tradeoff between array size and wind-induced movement. Generally, it is not possible to use larger arrays without risking a corresponding performance loss from wind-induced beam misalignment. The performance of the proposed alignment technique is analyzed and compared with other search and alignment methods. The results show significant performance improvement with reduced search time.

Reduced Feedback MIMO-OFDM Precoding and Antenna Selection

Transmitter precoding for multiple-input-multiple-output orthogonal frequency division multiplexing (MIMO-OFDM) is an effective way of leveraging the diversity gains afforded by a multiple-transmit multiple-receive antenna system in a frequency selective environment. In the limited feedback scenario, optimal precoder representation for narrowband MIMO systems using moderately sized codebooks designed on the Grassmann manifold has been shown to perform remarkably well. In MIMO-OFDM systems, precoder matrices have to be designed for all subcarriers and the amount of feedback can get prohibitively large. This is especially true for next generation wireless local area networks and wireless metropolitan area networks which have a large number of subcarriers. In this paper, we present techniques to reduce this feedback requirement and the performance of these algorithms is numerically shown to provide improvement over existing schemes

Optimum and suboptimum frame synchronization for pilot-symbol-assisted modulation

Pilot-symbol-assisted modulation (PSAM) is a method to reduce the effects of fading in mobile communications by periodically inserting known symbols in the data stream. The receiver uses these pilot symbols to derive its amplitude and phase reference. One aspect of this procedure which has not received much attention in the literature is the method used by the receiver to locate the pilot symbols. This paper uses optimum frame synchronization techniques to develop two synchronizers for PSAM systems; one is based on a standard maximum likelihood (ML) estimation formulation, and the other is a sequential testing algorithm. Both methods use a simple quadratic correlation filter with an energy correction factor. Simulation results and a theoretical analysis are presented.

Influence of Vertical Sensor Placement on Data Collection Efficiency from Bluetooth MAC Address Collection Devices

The consumer electronics industry has made extensive use of the Bluetooth wireless protocol in many portable devices. A substantial number of these Bluetooth devices broadcast a unique identifier in the form of the media access control (MAC) addresses. These MAC addresses can be captured electronically and the same matching algorithms used in traditional license plate studies can be used to estimate segment travel time and origin-destination matrices. This paper briefly illustrates how these data can be used to estimate arterial link travel times and empirically illustrates the sensitivity of sample size to sensor placement. A controlled experiment with fixed lateral mounting and varying vertical mounting heights is then conducted to develop design recommendations for mounting Bluetooth monitoring devices. The paper concludes by recommending a Class I Bluetooth detector mounting height of at least 8 ft above the pavement grade. Based on a 24-h empirical data set on I-65 in Indianapolis, we found that 7.4%...

Analysis and Practical Considerations in Implementing Multiple Transmitters for Wireless Power Transfer via Coupled Magnetic Resonance

Multiple transmitters can be used to simultaneously transmit power wirelessly to a single receiver via strongly coupled magnetic resonance. A simple circuit model is used to help explain the multiple-transmitter wireless power transfer system. Through this particular scheme, there is an increase in gain and “diversity” of the transmitted power according to the number of transmit coils. The effect of transmitter resonant coil coupling is also shown. Resonant frequency detuning due to nearby metallic objects is observed, and the extent of how much tuning can be done is demonstrated. A practical power line synchronization technique is proposed to synchronize all transmit coils, which reduces additional dedicated synchronization wiring or the addition of an RF front-end module to send the reference driving signal.

The stability of variable step-size LMS algorithms

Variable step-site LMS (VSLMS) algorithms are a popular approach to adaptive filtering, which can provide improved performance while maintaining the simplicity and robustness of conventional fixed step-size LMS. Here, we examine the stability of VSLMS with uncorrelated stationary Gaussian data. Most VSLMS described in the literature use a data-dependent step-size, where the step-size either depends on the data before the current time (prior step-size rule) or through the current time (posterior step-size rule). It has often been assumed that VSLMS algorithms are stable (in the sense of mean-square bounded weights), provided that the step-size is constrained to lie within the corresponding stability region for the LMS algorithm. For a single tap fitter, we find exact expressions for the stability region of VSLMS over the classes of prior and posterior step-sizes and show that the stability region for prior step size coincides with that of fixed step-size, but the region for posterior step-size is strictly smaller than for fixed step-size. For the multiple tap case, we obtain bounds on the stability regions with similar properties. The approach taken here is a generalization of the classical method of analyzing, the exponential stability of the weight covariance equation for LMS. Although it is not possible to derive a weight covariance equation for general data-dependent VSLMS, the weight variances can be upper bounded by the solution of a linear time-invariant difference equation, after appropriately dealing with certain nonlinear terms. For prior step-size (like fixed step-size), the state matrix is symmetric, whereas for posterior step-size, the symmetry is lost, requiring a more detailed analysis. The results are verified by computer simulations.

Noise-constrained least mean squares algorithm

We consider the design of an adaptive algorithm for finite impulse response channel estimation, which incorporates partial knowledge of the channel, specifically, the additive noise variance. Although the noise variance is not required for the offline Wiener solution, there are potential benefits (and limitations) for the learning behavior of an adaptive solution. In our approach, a Robbins-Monro algorithm is used to minimize the conventional mean square error criterion subject to a noise variance constraint and a penalty term necessary to guarantee uniqueness of the combined weight/multiplier solution. The resulting noise-constrained LMS (NCLMS) algorithm is a type of variable step-size LMS algorithm where the step-size rule arises naturally from the constraints. A convergence and performance analysis is carried out, and extensive simulations are conducted that compare NCLMS with several adaptive algorithms. This work also provides an appropriate framework for the derivation and analysis of other adaptive algorithms that incorporate partial knowledge of the channel.

Single frequency estimation with non-uniform sampling

A new frame structure is proposed for pilot symbol assisted modulation (PSAM) systems which includes a small number of known pilots at the start of each frame. This facilitates the estimation of large frequency offsets without aliasing. Cramer Rao lower bounds and the exact ML estimates are derived for AWGN and Rayleigh fading channels. Finally, simulations show that the ML estimator has much better performance than existing reduced complexity estimators when applied to this sparse observation model.

Multilevel millimeter wave beamforming for wireless backhaul

Due to the projected increased demand for high data rate mobile services, interest has grown in new cellular network architectures such as a tiered networks. This paper proposes a beam searching algorithm and a codebook design for multilevel beamforming in outdoor millimeter wave communication systems. In an outdoor millimeter wave scenario, the received signal suffers from severe path loss and various attenuation factors. Beamforming is an essential component to establish the wireless link in 60GHz up to 80GHz. A millimeter wave beamforming method based on joint transmitter-receiver searching of an adaptive codebook is described. To reduce search complexity, an adaptive beam width beamforming technique is developed based on a sub-array method using squinting angles. A multilevel codebook having a hierarchical tree-structure on different beam width is adaptively designed. The performance of the proposed codebook design is analyzed, and the joint search algorithm is compared with other search methods. The proposed search method and the codebook design show performance improvement with small complexity.

Model‐based vehicle tracking from image sequences with an application to road surveillance

A model-based approach to vehicle tracking is proposed and applied to a highway traffic surveillance problem, which is motivated by current research in intelligent transportation systems. Systems for traffic management and traveler information services require accurate and wide-area estimates of vehicle velocity and traffic spatial and temporal densities. A detection and tracking algorithm is developed that achieves good performance with complexity low enough for real-time implementation using inexpensive microprocessors. Detection thresholds are computed based on a statistical model for vehicle and background, and the theoretical detector performance is derived. The tracking algorithm filters position estimates from the detection algorithm using a simple vehicle dynamic model and the Kalman filter. Data association is accomplished with a nearest neighbor filter coupled with a lane-change handling logic.