Channel estimation and data detection for mobile MIMO OFDM systems

Designing spectral efficient, high-speed wireless links that offer high quality- of-service and range capability has been a critical research and engineering challenge. In this thesis, we mainly address the complexity and performance issues of channel estimation and data detection in multiple-input multiple-output (MIMO) orthogonal frequency division multiplexing (OFDM) systems over time-varying channels. We derive the probability density function (pdf) expressions of the condition number (i.e., the maximum-to-minimum-singular-value ratio, MMSVR) of the channel state information matrix of MIMO OFDM systems. It is shown that this ratio is directly related to the noise enhancement in open-loop systems and provides a significant insight on the system capacity. A decision-directed (DD) maximum a posteriori probability (MAP) channel estimation scheme of MIMO systems is derived. Error performance of a zero- forcing receiver with the DD MAP and perfect channel estimates is provided and compared. This scheme has a low complexity and can be applied to time-varying Rayleigh fading channels with an arbitrary spaced-time correlation function. We propose an iterative channel estimation and data detection scheme for MIMO OFDM systems in the presence of inter-carrier-interference (ICI) due to the nature of time-varying channels. An ICI-based minimum-mean-square error (MMSE) detection scheme is derived. An expectation-maximization (EM) based least square (LS) channel estimator is proposed to minimize the mean-square error (MSE) of the channel estimates and to reduce the complexity of the implementation. With the estimate of the channel and initially detected symbols, ICI is estimated and removed from the received signal. Thus more accurate estimation of the channel and data detection can be obtained in the next iteration. An EM-based MAP channel estimator is derived by exploiting the frequency/time correlation of the pilot and data sub-carriers. Performance comparison is made between the proposed schemes and the ideal case - time-invariant channels and perfect channel estimation. We optimize the data transmission by exploiting the long term correlation characteristics. The transmitted data is successively detected without an error floor in spatially correlated channels. The algorithms proposed in this thesis allow low-complexity implementation of channel estimation and data detection for MIMO OFDM systems over time-varying fading channels, while providing good error performance.Keywords: inter-carrier-interference, MIMO OFD

Performance Analysis and Optimal Power Allocation for Linear Receivers Based on Superimposed Training

In this paper, we derive a performance comparison between two training-based schemes for Multiple-Input Multiple-Output (MIMO) systems. The two schemes are thetime-division multiplexing scheme and the recently proposed data-dependent superimposed pilot scheme. For both schemes, a closed-form expressions for the Bit Error Rate (BER) is provided. We also determine, for both schemes, the optimal allocation of power between pilot and data that minimizes the BER

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

Antenna Combining for the MIMO Downlink Channel

A multiple antenna downlink channel where limited channel feedback is available to the transmitter is considered. In a vector downlink channel (single antenna at each receiver), the transmit antenna array can be used to transmit separate data streams to multiple receivers only if the transmitter has very accurate channel knowledge, i.e., if there is high-rate channel feedback from each receiver. In this work it is shown that channel feedback requirements can be significantly reduced if each receiver has a small number of antennas and appropriately combines its antenna outputs. A combining method that minimizes channel quantization error at each receiver, and thereby minimizes multi-user interference, is proposed and analyzed. This technique is shown to outperform traditional techniques such as maximum-ratio combining because minimization of interference power is more critical than maximization of signal power in the multiple antenna downlink. Analysis is provided to quantify the feedback savings, and the technique is seen to work well with user selection and is also robust to receiver estimation error.Comment: Submitted to IEEE Trans. Wireless Communications April 2007. Revised August 200

Metameric MIMO-OOK transmission scheme using multiple RGB LEDs

In this work, we propose a novel visible light communication (VLC) scheme utilizing multiple di erent red green and blue triplets each with a di erent emission spectrum of red, green and blue for mitigating the e ect of interference due to di erent colors using spatial multiplexing. On-o keying modulation is considered and its e ect on light emission in terms of flickering, dimming and color rendering is discussed so as to demonstrate how metameric properties have been considered. At the receiver, multiple photodiodes with color filter-tuned on each transmit light emitting diode (LED) are employed. Three di erent detection mechanisms of color zero forcing, minimum mean square error estimation and minimum mean square error equalization are then proposed. The system performance of the proposed scheme is evaluated both with computer simulations and tests with an Arduino board implementatio

MIMO Interference Alignment Over Correlated Channels with Imperfect CSI

Interference alignment (IA), given uncorrelated channel components and perfect channel state information, obtains the maximum degrees of freedom in an interference channel. Little is known, however, about how the sum rate of IA behaves at finite transmit power, with imperfect channel state information, or antenna correlation. This paper provides an approximate closed-form signal-to-interference-plus-noise-ratio (SINR) expression for IA over multiple-input-multiple-output (MIMO) channels with imperfect channel state information and transmit antenna correlation. Assuming linear processing at the transmitters and zero-forcing receivers, random matrix theory tools are utilized to derive an approximation for the post-processing SINR distribution of each stream for each user. Perfect channel knowledge and i.i.d. channel coefficients constitute special cases. This SINR distribution not only allows easy calculation of useful performance metrics like sum rate and symbol error rate, but also permits a realistic comparison of IA with other transmission techniques. More specifically, IA is compared with spatial multiplexing and beamforming and it is shown that IA may not be optimal for some performance criteria.Comment: 21 pages, 7 figures, submitted to IEEE Transactions on Signal Processin