Navid Lashkarian

Class of cyclic-based estimators for frequency-offset estimation of OFDM systems

We present a new class of blind cyclic-based estimators for carrier frequency-offset and symbol-timing error estimation of orthogonal frequency-division multiplexing (OFDM) systems. The proposed approach exploits the properties of the cyclic prefix subset to reveal the synchronization parameters in the likelihood function of the received vector. A new likelihood function for the joint timing and frequency-offset estimation is derived, which globally characterizes the estimation problem. The resulting probabilistic measure is used to develop three classes of unbiased estimators, namely, maximum-likelihood, minimum variance unbiased, and moment estimator. In comparison to the previously proposed methods, the proposed estimators in this study are computationally and statistically efficient, which makes the estimators more attractive for real-time applications. The performance of the estimators is assessed by simulation for an OFDM system.

Optimum equalization of multicarrier systems: a unified geometric approach

This paper presents a new iterative equalization algorithm that maximizes the capacity for discrete multitone (DMT) systems. The research modifies a previously proposed criterion and applies an appropriate transformation to map the objective function and the constraint set into a canonical region. The resulting constraint set exhibits an identifiable geometric characteristic. Using the gradient projection method in conjunction with projection onto convex sets (POCS) provides us with an iterative search algorithm that facilitates the gradient descent method. We also generalize the approach to two important subclasses of equalizers, namely linear phase and unit tap filters. We also derive a fundamental limit on the performance of the proposed approach. In comparison with the previous methods, the proposed equalization algorithm is less computationally complex and more geometrically intuitive. Simulation experiments confirm the validity of the proposed method for equalization of DMT systems.

Reconfigurable Digital Front-End Hardware for Wireless Base-Station Transmitters: Analysis, Design and FPGA Implementation

A versatile digital front-end architecture is designed and implemented on field-programmable gate array (FPGA) technology. The architecture includes the digital up-conversion, and peak-to-average power ratio (PAPR) reduction blocks that are applicable to down-link data paths in multi-band wireless base stations such as WCDMA or Wimax systems. Transmitter linearity requirements are addressed and tradeoff analysis for design and optimization of the PAPR reduction algorithm within the context of the error vector magnitude and adjacent channel leakage ratio quality metrics are studied. Statistical characteristics of the clipping noise are analyzed and a novel method for clipping the multi-band signal under the phase invariant constraint is proposed. Our study also includes mapping of the signal processing algorithms onto Xilinx Virtex-4trade FPGA device and addresses the resource utilization and efficient hardware implementation of the above signal processing blocks. Performance assessments and hardware validation of the proposed architecture are also addressed.

A Direct Learning Adaptive Scheme for Power-Amplifier Linearization Based on Wirtinger Calculus

Performance of radio frequency power amplifiers is often significantly degraded by nonlinearity and memory effects. We study the applicability of complex-domain adaptive filtering to the problem of predistortion kernel learning for power-amplifier linearization. The least-squares error function that arises while deriving the optimal predistortion function is often real with complex-valued arguments, therefore, nonanalytic in the Cauchy-Riemann sense. To avoid the strict Cauchy-Riemann differentiability condition for non-holomorphic functions (e.g. mean-square error), we resort to the theory of Wirtinger calculus, which allows construction of differential operators in a way that is analogous to functions of real variables. By deploying the new differential operators, digital pre-distortion coefficient optimization is carried out in a space isomorphic to the real vector space, at a computational complexity that is significantly lower than that of the real space. We also derive proper Hessian forms for minimization of the objective function and propose a variety of descent-update algorithms, namely Newton, Gauss-Newton, and their quasi-equivalent variants for this problem. Performance assessments and experimental validation of the proposed methodologies are also addressed.

Performance Bound on Ergodic Capacity of MIMO Beam-Forming in Indoor Multi-Path Channels

This paper aims to characterize the ergodic capacity of multiple input multiple output (MIMO) antenna beam-forming in indoor multi-path propagation environments. Using Double-Directional Cluster-Ray (DDCR) channel models, the second order statistics of the strongest eigen-mode of the channel is analyzed. An upper bound on the ergodic capacity of the MIMO beam-forming is derived and the impact of channel propagation parameters, such as cluster/ray arrival rates and power decay profiles, on this upper bound is investigated. The theoretical results are subsequently applied to estimate the capacity of the next generation very high throughput WLAN at the 60 GHz frequency band.

Statistical Characterization of Power Amplifier Nonlinearity at 60 GHz: MIMO Beam-forming Analysis

This paper presents an analytical framework to model and characterize the power amplifier nonlinearity at 60 GHz. Using extension of Bussgang theorem, we propose a closed form expression for the variance of power amplifier nonlinearity noise as a function of the power amplifier output backoff. The variance is subsequently used to estimate the capacity of MIMO beam-forming subject to the power amplifier nonlinearity at the transmitter.

Direct learning adaptation of power amplifier pre-distortion based on Wirtinger calculus

To improve efficiency of power amplifier (PA), linearity characteristics is often compromised when targeting lower power consumption (class B). Moreover, sophisticated PA efficiency improvement schemes such as envelope tracking tend to further boost the nonlinear characteristics of the PA. Digital pre-distortion (DPD) is a technique to improve the linearity of a power amplifier (PA) at expense of extra processing in the base-band. Derivation of optimal DPD adaptive learning involves optimization of real-valued objective functions of complex variables, whose derivative or gradient does not exist in the standard complex-analysis sense, due to non-holomorphic nature of the function. This is often overlooked in the literature and results in erroneous results. For instance, the methodology presented in [8] computes the gradient with respect to the variable to compute the updates. However, as discussed in [3] and [1], it is the gradient with respect to the conjugate of the variable (and not the variable) that leads to the nonpositive increment of the objective function. We resort to the theory of Wirtinger calculus to derive the proper first-and second-order derivatives (gradient and Hessian operators) of the non-holomorphic objective function and extend the results to optimization methodologies such as Newton, Gauss-Newton, and their quasi-variants. Results are assessed through experimental validation of the proposed methods on WLAN PAs.

MIMO Beam-forming at 60 GHz: Analysis of Ergodic Capacity

This paper aims to characterize the ergodic capacity of multiple input multiple output (MIMO) antenna beam-forming in indoor multi-path propagation environments. Using Double Directional Cluster Ray (DDCR) channel models, the second order statistics of the strongest eigen-mode of the channel is analyzed. An upper bound on the ergodic capacity of the MIMO beam-forming is derived and the impact of channel propagation parameters, such as cluster/ray arrival rates and power decay profiles, on the ergodic capacity is investigated. The theoretical results are subsequently applied to estimate the capacity of the next generation very high throughput WLAN at the 60 GHz frequency band.