James Dunyak

Performance of a joint Kalman demodulator for multiuser detection

Long code asynchronous CDMA provides a significant challenge, especially when the system is operating at high capacity. We describe a Kalman filter technique that estimates the channel coefficients while demodulating the multiuser signal. A state-space signal model is derived when multiple sources each provide a pilot and numerous user channels, as described by IS95. A numerically efficient algorithm is proposed which estimates each source disjointly but provides interference cancellation through the innovations. A Rayleigh fading model based on Jakes (1974) model is used to describe a time-varying channel. Performance is then demonstrated at high capacity and compared to the conventional detector.

Enhancing the performance of wireless sensor networks with MIMO communications

Wireless sensor networks are an enabling technology for many future surveillance-oriented applications. Before a practical wireless sensor network is realized, however, significant challenges must be overcome. Chief among the obstacles to netted sensors is providing low power, robust communications between sensor nodes. Multiple input, multiple output (MIMO) communication promises performance enhancements over conventional single input, single output (SISO) technology for the same radiated power. If leveraged in a sensor network, MIMO may be able to provide significant network performance improvements in power consumption, latency, and network robustness. The application of MIMO to wireless sensor networks was explored in J. Burdin et al. (2005) with regard to probability of cohesion and largest cluster sizes. This paper investigates the benefit of MIMO implementations in multihop wireless sensor networks in terms of the mean path length. We find that MIMO provides improvement to wireless sensor networks, particularly those that have low to midrange node densities

Models, prediction, and estimation of outbreaks of infectious disease

Conventional SEIR (susceptible-exposed-infectious-recovered) models have been utilized by numerous researchers to study and predict disease outbreak. By combining the predictive nature of such mathematical models along with the measured occurrences of disease, a more robust estimate of disease progression can be made. The Kalman filter is the method designed to incorporate model prediction and measurement correction. Consequently, we produce an SEIR model which governs the short term behaviour of an epidemic outbreak. The mathematical structure for an associated Kalman filter is developed and estimates of a simulated outbreak are provided.

A steady state decoupled Kalman filter technique for multiuser detection

In this paper, we describe a Kalman filter based technique for multiuser detection of asynchronous CDMA systems. Similar to previously proposed techniques, we use a decoupled form of the Kalman filter, which processes each user independently. We then make the further simplifying assumption that the channel statistics are constant over a single symbol allowing us to reduce the Kalman gain to a constant dependent on the current signal to interference plus noise ratio. We study the performance of the constant gain filter and show that by appropriate choice of the gain you can optimize for either minimum bit error rate or maximum interference reduction.

Cohesion of wireless sensor networks with MIMO communications

Wireless sensor networks are an enabling technology for many future surveillance-oriented applications. Before a practical wireless sensor network is realized, however, significant challenges must be overcome. Chief among the obstacles to netted sensors is providing low power, robust communications between sensor nodes. Multiple input, multiple output (MIMO) communication promises performance enhancements over conventional single input, single output (SISO) technology for the same radiated power. If leveraged in a sensor network, MIMO may be able to provide significant network performance improvements in power consumption, latency, and network robustness. However, improvements in the physical layer are not always realized in the higher layers. This paper investigates the benefit of MIMO implementations in multihop wireless sensor networks in terms of network cohesion - that is, the ability of the sensor nodes to form a completely connected network.

Cooperative MIMO gateways: a promising technique for fast handoff

The multi-input multi-output (MIMO) technique has been portrayed as the next revolution for wireless technologies. The MIMO technique is an effective mechanism to increase capacity and reliability of wireless communications by taking advantage of its spatial multiplexing gain or diversity gain. However, conventional MIMO is expensive: the form factor of the radio is large, multiple RF front ends are required, multiple antennas can be difficult to place on a mobile platform, and the parallel propagation channels may be correlated. The paper investigates an alternative way of implementing MIMO: cooperative MIMO, where multiple nodes coordinate their transmissions so that cooperative parallel transmissions can be established between multiple source nodes and a destination node, and space/time coding is applied on the transmissions. We not only investigate the capacity gain from using cooperative MIMO, we also use cooperative MIMO to perform fast handoff for wireless networks. The performance of the proposed fast handoff approach is evaluated using modeling and simulation (M&S).

Multiuser CDMA with a chip-level interference cancellation technique

Multiple-access interference (MAI) limits the performance of CDMA systems using the conventional receiver, but the optimal receiver is too complex for practical implementation. This paper demonstrates a numerically efficient technique for reducing MAI in CDMA systems. The technique, a nonlinear approach inspired by the Kalman filter, uses decoupled filters to estimate symbols for each user while accomplishing interference cancellation in the innovation term. The filter technique developed here provides a computationally practical approach to multiuser detection for asynchronous long code systems, which significantly outperforms the conventional receiver. Kalman filter approaches to multiuser detection have been applied before (Lim and Ma 2000, Lim et. al. 1998) to binary phase shift keying through implementation of a standard Kalman filter approach. Unfortunately, this leads to high computational complexity. Here, we instead consider a formulation in which the spreading codes are viewed as random and their properties are used to decouple the Kalman filter for each user. Interference cancellation is then implemented through the innovations. A binary minimum mean squared error estimate is made, which results in a nonlinear estimator. The new nonlinear technique is shown to significantly outperform an optimized partial parallel interference cancellation approach, which is the current state of the art technique for asynchronous long code systems. System capacity is then significantly increased.

A low complexity adaptive beamformer for OFDM

Because of ease of implementation and robustness to multipath delay spread, orthogonal frequency division multiplexing is an increasing popular technology for ad hoc networks. Unfortunately, OFDM performs poorly in the presence of cochannel interference, which degrades network capacity. In this paper, we develop beamforming techniques which minimize cochannel interference to allow spatial division multiple access. The standard approaches in the literature develop a separate beamformer for each narrowband carrier, with perhaps some grouping based on coherence across frequencies. This approach is both computationally complex and, as shown in this paper, difficult in an outdoor environment with expected Doppler spread. Here, we develop a time domain beamformer with low complexity and more robustness to a changing channel. Performance is demonstrated with multipath angular and Doppler spreads typical of mobile uplinks.