Khurram Waheed received his B.Sc.(Hons.) in Electrical Engineering from University of Engineering and Technology, Lahore, Pakistan (1994) and both his M.S. (2000) and Ph.D. (2003) in Electrical Engineering from Michigan State University. From 1994 to 2003, he worked on various challenging industrial and academic research projects. During 2003-04, he was a faculty at San Diego State University. From 2004 to 2010, he lead 2G/3G/4G cellular radio design system architecture teams at Texas Instruments Inc., Dallas (2004-09) and Bitwave Semiconductors, MA (2009-10). Since 2010, he has been with Freescale/NXP, where he is currently an NXP fellow and leads system architecture activities for the connectivity portfolio. Dr. Waheed has published more than 75 technical papers and holds 50 granted patents. His research interests include novel digitally-assisted radio architectures and circuits, adaptive learning techniques, blind and adaptive signal processing algorithms, MIMO systems and non-linear control
2010 IEEE International Solid-State Circuits Conference - (ISSCC), 2010
A 0.8 mm2 small-signal polar EDGE TX, part of a 65 nm CMOS SoC, incorporates a fully-digital impl... more A 0.8 mm2 small-signal polar EDGE TX, part of a 65 nm CMOS SoC, incorporates a fully-digital implementation for the amplitude path meeting the strict emission mask without a SAW filter. Various RF impairments in the AM circuitry are digitally compensated, resulting in 2.5% rms EVM (high-band, HB) and over 8 dB margin with the close-in mask. The TX consumes
ABSTRACT A digitally controlled mechanism for the minimization of the self-interference caused by... more ABSTRACT A digitally controlled mechanism for the minimization of the self-interference caused by an amplitude modulated signal generated within a polar transmitter to the oscillator circuit, where the carrier of that transmitter is created. A digitally controlled delay between the circuit where the signal is generated and the circuit where it is amplitude-modulated allows adjustment of the delay or phase-shift between the aggressing and victim signals. The optimal delay that is to be introduced in the path is determined, and a corresponding control word is generated to arrive at the selected delay/phase-shift.
This paper presents two separate structures for the blind source recovery (BSR) of stochastically... more This paper presents two separate structures for the blind source recovery (BSR) of stochastically independent signal sources. We hypothesize linear state space models for both the mixing environment and the demixing (i.e. recovering) adaptive network. Separate algorithms for adaptive estimation of parameters for the feedforward and feedback recovering networks have been derived. Auxillay conditions for the convergence of these algorithms have also been derived and discussed. Simulation examples have been included to compare the results for both algorithms for an IIR mixing environment. Conclusive remarks about effectiveness of these techniques in various practical problems have also been included.
Algebraic Independent Component Analysis (AICA) is a new ICA algorithm that exploits algebraic op... more Algebraic Independent Component Analysis (AICA) is a new ICA algorithm that exploits algebraic operations and vectordistance measures to estimate the unknown mixing matrix in a scaled algebraic domain. AICA possesses stability and convergence properties similar to earlier proposed geometic ICA (geo-ICA) algorithms, however, the choice of the proposed algebraic measures in AICA has several advantages. Firstly, it leads to considerable reduction in the computational complexity of the AICA algorithm as compared to similar algorithms relying on geometric measures making AICA more suitable for online implementations. Secondly, algebraic operations exhibit robustness against the inherent permutation and scaling issues in ICA, which simplifies the performance evaluation of the ICA algorithms using algebraic measures. Thirdly, the algebraic framework is directly extendable to any dimension of ICA problems exhibiting only a linear increase in the computational cost as a function of the mixin...
The paper provides an overview of the development of a self-learning computing chip in the new 0.... more The paper provides an overview of the development of a self-learning computing chip in the new 0.18 micron copper technology. The chip realizes an architecture that achieves the task of self-learning execution times in the micro to milli seconds. The core consists of basic building blocks of 4-quadrant multipliers, trans-conductance amplifiers, and active load resistances, for analog (forward-) network processing and learning modules. Super-imposed on the processing network are digital memory and control modules composed of D-Flip-flops, ADC, Multiplying D/A Converter (MDAC), and comparators for parameter (weight) storage, logical control and analog/digital conversions. The single System-on-Chip design impacts several domains of critical applications that include nano-scale biotechnology, automotive sensing, control and actuation, wireless communications, image feature extraction and pattern matching etc 1.
which permits unrestricted use, distribution, and reproduction in any medium, provided the origin... more which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. Digital predistortion is an effective means to compensate for the nonlinear effects of a memoryless system. In case of a cellular transmitter, a digital baseband predistorter can mitigate the undesirable nonlinear effects along the signal chain, particularly the nonlinear impairments in the radiofrequency (RF) amplifiers. To be practically feasible, the implementation complexity of the predistorter must be minimized so that it becomes a cost-effective solution for the resource-limited wireless handset. This paper proposes optimizations that facilitate the design of a low-cost high-performance adaptive digital baseband predistorter for memoryless systems. A comparative performance analysis of the amplitude and power lookup table (LUT) indexing schemes is presented. An optimized low-complexity amplitude approximation and its hardware synthesis results are also st...
Blind Source Recovery (BSR) is an interesting autonomous and unsupervised stochastic adaptation p... more Blind Source Recovery (BSR) is an interesting autonomous and unsupervised stochastic adaptation problem that includes the well-known blind adaptive problems of Blind Source Separation (BSS), Deconvolution (BSD) and Equalization (BSE). BSR includes also the nonlinear case and hences focuses on reproducing or estimating the source signals even if environment identifiction is not achieved. A number of outstanding research contributions have been made in this field, however, the issues of application are still in their infancy. Most of the BSR algorithms have characteristics, which make them suitable for a particular subclass of problems. In order to develop a generalized source recovery framework and yet achieve optimal performance in all cases, there is a need to explore further architectural and/or algorithmic domains. In this paper, we approach this goal in the architecture domain by focusing on the use of cascaded structures for BSR. The paper discusses the need, choice, possible f...
This paper discusses the implementation of our proposed algorithms for Blind source Recovery base... more This paper discusses the implementation of our proposed algorithms for Blind source Recovery based on constrained optimization using the state-space framework. Two simulation examples are presented where the mixing environment is modeled as FIR and IIR, respectively. The rate of convergence using the proposed implementation for these particular environment models is compared for various classes of data. Conclusions are derived for effectiveness of these techniques in various practical problems.
The demand for energy is growing at an unprecedented pace that is much higher than the energy gen... more The demand for energy is growing at an unprecedented pace that is much higher than the energy generation capacity growth rate using both conventional and green technologies.In particular, the electric power sector is consistently rated among the most dynamic growth markets over all other energy markets. Distributed (decentralized) energy generation based on renewable energy sources is an efficient and reliable solution to serve such huge energy demand growth [1]. However, to manage dynamic and complex distributed systems, a massive amount of data has to be measured, collected, exchanged and processed in real time. Smart grids manage an intelligent energy delivery network enabled two-way communications between data concentrators operated by utility companies and smart meters installed at the end users. In particular, dynamic power-grid loading and peak load management are the two main driving forces for bidirectional communications over the grid. Narrowband power line communications ...
IEEE Transactions on Circuits and Systems Ii-express Briefs, 2015
Within the framework of a radio-frequency all- digital phase-locked loop, the frequency tuning of... more Within the framework of a radio-frequency all- digital phase-locked loop, the frequency tuning of a digitally con- trolled oscillator (DCO) is realized using switchable capacitors (varactors). The minimum feature size and lithographic mismatch of these varactors limit the physical frequency resolution of the DCO to tens of kilohertz. To satisfy the fine frequency resolution of hundreds of hertz in wireless cellular and connectivity standards, high-speed sigma-delta (ΣΔ) frequency dithering is convention- ally employed to improve the time-averaged DCO resolution by at least two orders of magnitude. Unfortunately, the dithering characteristics of the ΣΔ modulator vary depending on its frac- tional frequency input and the physical and timing mismatches in the mapping of the multibit digital output to the frequency. This brief investigates the dithering mechanisms that are a potential source of the spurious corruption of the DCO output spectrum and proposes a set of enhancements to miti...
Proceedings of the 2003 International Symposium on Circuits and Systems 2003 Iscas 03, 2003
We present two new hyperbolic source probability models to effectively represent sub-gaussian and... more We present two new hyperbolic source probability models to effectively represent sub-gaussian and super-gaussian families of sources for dynamic and convolutive Blind Source Recovery (BSR). Both models share a common boundary for the gaussian density function. The proposed hyperbolic probability model for the sub-gaussian densities is an extension of the Pearson density model. The model can represent a broader range
2004 Ieee International Symposium on Circuits and Systems, 2004
ABSTRACT This paper revisits the issue of blind source recovery (BSR) of non-minimum phase linear... more ABSTRACT This paper revisits the issue of blind source recovery (BSR) of non-minimum phase linear MIMO systems and provides a new rigorous derivation of the proposed state space algorithms by K. Waheed and F.M. Salem (2002), K. Waheed F.M. Salem (2003) and L.Q. Zhang et al. (1999). Using state space representation for both the mixing and convolving (or reverberative) surrounding environment and recovery (or demixing and deconvolving) networks, we systematically derive update laws based on the minimization of Kullback-Liebler divergence using the theory of optimization and the calculus of variations along the Riemannian contra-variant (or the natural) gradient. A simulation example for recovery of signals from a challenging non-minimum environment is also included in this paper.
2010 IEEE International Solid-State Circuits Conference - (ISSCC), 2010
A 0.8 mm2 small-signal polar EDGE TX, part of a 65 nm CMOS SoC, incorporates a fully-digital impl... more A 0.8 mm2 small-signal polar EDGE TX, part of a 65 nm CMOS SoC, incorporates a fully-digital implementation for the amplitude path meeting the strict emission mask without a SAW filter. Various RF impairments in the AM circuitry are digitally compensated, resulting in 2.5% rms EVM (high-band, HB) and over 8 dB margin with the close-in mask. The TX consumes
ABSTRACT A digitally controlled mechanism for the minimization of the self-interference caused by... more ABSTRACT A digitally controlled mechanism for the minimization of the self-interference caused by an amplitude modulated signal generated within a polar transmitter to the oscillator circuit, where the carrier of that transmitter is created. A digitally controlled delay between the circuit where the signal is generated and the circuit where it is amplitude-modulated allows adjustment of the delay or phase-shift between the aggressing and victim signals. The optimal delay that is to be introduced in the path is determined, and a corresponding control word is generated to arrive at the selected delay/phase-shift.
This paper presents two separate structures for the blind source recovery (BSR) of stochastically... more This paper presents two separate structures for the blind source recovery (BSR) of stochastically independent signal sources. We hypothesize linear state space models for both the mixing environment and the demixing (i.e. recovering) adaptive network. Separate algorithms for adaptive estimation of parameters for the feedforward and feedback recovering networks have been derived. Auxillay conditions for the convergence of these algorithms have also been derived and discussed. Simulation examples have been included to compare the results for both algorithms for an IIR mixing environment. Conclusive remarks about effectiveness of these techniques in various practical problems have also been included.
Algebraic Independent Component Analysis (AICA) is a new ICA algorithm that exploits algebraic op... more Algebraic Independent Component Analysis (AICA) is a new ICA algorithm that exploits algebraic operations and vectordistance measures to estimate the unknown mixing matrix in a scaled algebraic domain. AICA possesses stability and convergence properties similar to earlier proposed geometic ICA (geo-ICA) algorithms, however, the choice of the proposed algebraic measures in AICA has several advantages. Firstly, it leads to considerable reduction in the computational complexity of the AICA algorithm as compared to similar algorithms relying on geometric measures making AICA more suitable for online implementations. Secondly, algebraic operations exhibit robustness against the inherent permutation and scaling issues in ICA, which simplifies the performance evaluation of the ICA algorithms using algebraic measures. Thirdly, the algebraic framework is directly extendable to any dimension of ICA problems exhibiting only a linear increase in the computational cost as a function of the mixin...
The paper provides an overview of the development of a self-learning computing chip in the new 0.... more The paper provides an overview of the development of a self-learning computing chip in the new 0.18 micron copper technology. The chip realizes an architecture that achieves the task of self-learning execution times in the micro to milli seconds. The core consists of basic building blocks of 4-quadrant multipliers, trans-conductance amplifiers, and active load resistances, for analog (forward-) network processing and learning modules. Super-imposed on the processing network are digital memory and control modules composed of D-Flip-flops, ADC, Multiplying D/A Converter (MDAC), and comparators for parameter (weight) storage, logical control and analog/digital conversions. The single System-on-Chip design impacts several domains of critical applications that include nano-scale biotechnology, automotive sensing, control and actuation, wireless communications, image feature extraction and pattern matching etc 1.
which permits unrestricted use, distribution, and reproduction in any medium, provided the origin... more which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. Digital predistortion is an effective means to compensate for the nonlinear effects of a memoryless system. In case of a cellular transmitter, a digital baseband predistorter can mitigate the undesirable nonlinear effects along the signal chain, particularly the nonlinear impairments in the radiofrequency (RF) amplifiers. To be practically feasible, the implementation complexity of the predistorter must be minimized so that it becomes a cost-effective solution for the resource-limited wireless handset. This paper proposes optimizations that facilitate the design of a low-cost high-performance adaptive digital baseband predistorter for memoryless systems. A comparative performance analysis of the amplitude and power lookup table (LUT) indexing schemes is presented. An optimized low-complexity amplitude approximation and its hardware synthesis results are also st...
Blind Source Recovery (BSR) is an interesting autonomous and unsupervised stochastic adaptation p... more Blind Source Recovery (BSR) is an interesting autonomous and unsupervised stochastic adaptation problem that includes the well-known blind adaptive problems of Blind Source Separation (BSS), Deconvolution (BSD) and Equalization (BSE). BSR includes also the nonlinear case and hences focuses on reproducing or estimating the source signals even if environment identifiction is not achieved. A number of outstanding research contributions have been made in this field, however, the issues of application are still in their infancy. Most of the BSR algorithms have characteristics, which make them suitable for a particular subclass of problems. In order to develop a generalized source recovery framework and yet achieve optimal performance in all cases, there is a need to explore further architectural and/or algorithmic domains. In this paper, we approach this goal in the architecture domain by focusing on the use of cascaded structures for BSR. The paper discusses the need, choice, possible f...
This paper discusses the implementation of our proposed algorithms for Blind source Recovery base... more This paper discusses the implementation of our proposed algorithms for Blind source Recovery based on constrained optimization using the state-space framework. Two simulation examples are presented where the mixing environment is modeled as FIR and IIR, respectively. The rate of convergence using the proposed implementation for these particular environment models is compared for various classes of data. Conclusions are derived for effectiveness of these techniques in various practical problems.
The demand for energy is growing at an unprecedented pace that is much higher than the energy gen... more The demand for energy is growing at an unprecedented pace that is much higher than the energy generation capacity growth rate using both conventional and green technologies.In particular, the electric power sector is consistently rated among the most dynamic growth markets over all other energy markets. Distributed (decentralized) energy generation based on renewable energy sources is an efficient and reliable solution to serve such huge energy demand growth [1]. However, to manage dynamic and complex distributed systems, a massive amount of data has to be measured, collected, exchanged and processed in real time. Smart grids manage an intelligent energy delivery network enabled two-way communications between data concentrators operated by utility companies and smart meters installed at the end users. In particular, dynamic power-grid loading and peak load management are the two main driving forces for bidirectional communications over the grid. Narrowband power line communications ...
IEEE Transactions on Circuits and Systems Ii-express Briefs, 2015
Within the framework of a radio-frequency all- digital phase-locked loop, the frequency tuning of... more Within the framework of a radio-frequency all- digital phase-locked loop, the frequency tuning of a digitally con- trolled oscillator (DCO) is realized using switchable capacitors (varactors). The minimum feature size and lithographic mismatch of these varactors limit the physical frequency resolution of the DCO to tens of kilohertz. To satisfy the fine frequency resolution of hundreds of hertz in wireless cellular and connectivity standards, high-speed sigma-delta (ΣΔ) frequency dithering is convention- ally employed to improve the time-averaged DCO resolution by at least two orders of magnitude. Unfortunately, the dithering characteristics of the ΣΔ modulator vary depending on its frac- tional frequency input and the physical and timing mismatches in the mapping of the multibit digital output to the frequency. This brief investigates the dithering mechanisms that are a potential source of the spurious corruption of the DCO output spectrum and proposes a set of enhancements to miti...
Proceedings of the 2003 International Symposium on Circuits and Systems 2003 Iscas 03, 2003
We present two new hyperbolic source probability models to effectively represent sub-gaussian and... more We present two new hyperbolic source probability models to effectively represent sub-gaussian and super-gaussian families of sources for dynamic and convolutive Blind Source Recovery (BSR). Both models share a common boundary for the gaussian density function. The proposed hyperbolic probability model for the sub-gaussian densities is an extension of the Pearson density model. The model can represent a broader range
2004 Ieee International Symposium on Circuits and Systems, 2004
ABSTRACT This paper revisits the issue of blind source recovery (BSR) of non-minimum phase linear... more ABSTRACT This paper revisits the issue of blind source recovery (BSR) of non-minimum phase linear MIMO systems and provides a new rigorous derivation of the proposed state space algorithms by K. Waheed and F.M. Salem (2002), K. Waheed F.M. Salem (2003) and L.Q. Zhang et al. (1999). Using state space representation for both the mixing and convolving (or reverberative) surrounding environment and recovery (or demixing and deconvolving) networks, we systematically derive update laws based on the minimization of Kullback-Liebler divergence using the theory of optimization and the calculus of variations along the Riemannian contra-variant (or the natural) gradient. A simulation example for recovery of signals from a challenging non-minimum environment is also included in this paper.
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