MIMO-OFDM communication systems: channel estimation and wireless location

In this new information age, high data rate and strong reliability features our wireless communication systems and is becoming the dominant factor for a successful deployment of commercial networks. MIMO-OFDM (multiple input multiple output-orthogonal frequency division multiplexing), a new wireless broadband technology, has gained great popularity for its capability of high rate transmission and its robustness against multi-path fading and other channel impairments. A major challenge to MIMO-OFDM systems is how to obtain the channel state information accurately and promptly for coherent detection of information symbols and channel synchronization. In the first part, this dissertation formulates the channel estimation problem for MIMO-OFDM systems and proposes a pilot-tone based estimation algorithm. A complex equivalent base-band MIMO-OFDM signal model is presented by matrix representation. By choosing equally-spaced and equally-powered pilot tones from sub-carriers in one OFDM symbol, a down-sampled version of the original signal model is obtained. Furthermore, this signal model is transformed into a linear form solvable for the LS (least-square) estimation algorithm. Based on the resultant model, a simple pilot-tone design is proposed in the form of a unitary matrix, whose rows stand for different pilot-tone sets in the frequency domain and whose columns represent distinct transmit antennas in the spatial domain. From the analysis and synthesis of the pilot-tone design in this dissertation, our estimation algorithm can reduce the computational complexity inherited in MIMO systems by the fact that the pilot-tone matrix is essentially a unitary matrix, and is proven an optimal channel estimator in the sense of achieving the minimum MSE (mean squared error) of channel estimation for a fixed power of pilot tones. In the second part, this dissertation addresses the wireless location problem in WiMax (worldwide interoperability for microwave access) networks, which is mainly based on the MIMO-OFDM technology. From the measurement data of TDOA (time difference of arrival), AOA (angle of arrival) or a combination of those two, a quasi-linear form is formulated for an LS-type solution. It is assumed that the observation data is corrupted by a zero-mean AWGN (additive white Gaussian noise) with a very small variance. Under this assumption, the noise term in the quasi-liner form is proved to hold a normal distribution approximately. Hence the ML (maximum-likelihood) estimation and the LS-type solution are equivalent. But the ML estimation technique is not feasible here due to its computational complexity and the possible nonexistence of the optimal solution. Our proposed method is capable of estimating the MS location very accurately with a much less amount of computations. A final result of the MS (mobile station) location estimation, however, cannot be obtained directly from the LS-type solution without bringing in another independent constraint. To solve this problem, the Lagrange multiplier is explored to find the optimal solution to the constrained LS-type optimization problem

AirSync: Enabling Distributed Multiuser MIMO with Full Spatial Multiplexing

The enormous success of advanced wireless devices is pushing the demand for higher wireless data rates. Denser spectrum reuse through the deployment of more access points per square mile has the potential to successfully meet the increasing demand for more bandwidth. In theory, the best approach to density increase is via distributed multiuser MIMO, where several access points are connected to a central server and operate as a large distributed multi-antenna access point, ensuring that all transmitted signal power serves the purpose of data transmission, rather than creating "interference." In practice, while enterprise networks offer a natural setup in which distributed MIMO might be possible, there are serious implementation difficulties, the primary one being the need to eliminate phase and timing offsets between the jointly coordinated access points. In this paper we propose AirSync, a novel scheme which provides not only time but also phase synchronization, thus enabling distributed MIMO with full spatial multiplexing gains. AirSync locks the phase of all access points using a common reference broadcasted over the air in conjunction with a Kalman filter which closely tracks the phase drift. We have implemented AirSync as a digital circuit in the FPGA of the WARP radio platform. Our experimental testbed, comprised of two access points and two clients, shows that AirSync is able to achieve phase synchronization within a few degrees, and allows the system to nearly achieve the theoretical optimal multiplexing gain. We also discuss MAC and higher layer aspects of a practical deployment. To the best of our knowledge, AirSync offers the first ever realization of the full multiuser MIMO gain, namely the ability to increase the number of wireless clients linearly with the number of jointly coordinated access points, without reducing the per client rate.Comment: Submitted to Transactions on Networkin

Channel Estimation and Optimal Pilot Signals for Universal Filtered Multi-Carrier (UFMC) Systems

We propose channel estimation algorithms and pilot signal optimization for the universal filtered multi-carrier (UFMC) system based on the comb-type pilot pattern. By considering the least square linear interpolation (LSLI), discrete Fourier transform (DFT), minimum mean square error (MMSE) and relaxed MMSE (RMMSE) channel estimators, we formulate the pilot signals optimization problem by minimizing the estimation MSE subject to the power constraint on pilot tones. The closed-form optimal solutions and minimum MSE are derived for LSLI, DFT, MMSE and RMMSE estimators