Multipath Polyphase Circuits and their Application to RF Transceivers

Nonlinearity and time-variance in radio frequency (RF) circuits leads to unwanted harmonics and intermodulation products, e.g. in power amplifiers and mixers. This paper reviews a recently proposed multipath polyphase circuit technique which can cancel such harmonics and intermodulation products. This will be illustrated using a power upconverter IC as an example. The upconverter works from DC to 2.4 GHz, and the multipath polyphase technique cleans its spectrum up to the 17th harmonic, keeping unwanted spurious responses more than 40dB below the carrier. The technique can also be useful for other applications, and some possible applications will be discussed

Sub-Nyquist Sampling: Bridging Theory and Practice

Sampling theory encompasses all aspects related to the conversion of continuous-time signals to discrete streams of numbers. The famous Shannon-Nyquist theorem has become a landmark in the development of digital signal processing. In modern applications, an increasingly number of functions is being pushed forward to sophisticated software algorithms, leaving only those delicate finely-tuned tasks for the circuit level. In this paper, we review sampling strategies which target reduction of the ADC rate below Nyquist. Our survey covers classic works from the early 50's of the previous century through recent publications from the past several years. The prime focus is bridging theory and practice, that is to pinpoint the potential of sub-Nyquist strategies to emerge from the math to the hardware. In that spirit, we integrate contemporary theoretical viewpoints, which study signal modeling in a union of subspaces, together with a taste of practical aspects, namely how the avant-garde modalities boil down to concrete signal processing systems. Our hope is that this presentation style will attract the interest of both researchers and engineers in the hope of promoting the sub-Nyquist premise into practical applications, and encouraging further research into this exciting new frontier.Comment: 48 pages, 18 figures, to appear in IEEE Signal Processing Magazin

The Expanded Very Large Array

In almost 30 years of operation, the Very Large Array (VLA) has proved to be a remarkably flexible and productive radio telescope. However, the basic capabilities of the VLA have changed little since it was designed. A major expansion utilizing modern technology is currently underway to improve the capabilities of the VLA by at least an order of magnitude in both sensitivity and in frequency coverage. The primary elements of the Expanded Very Large Array (EVLA) project include new or upgraded receivers for continuous frequency coverage from 1 to 50 GHz, new local oscillator, intermediate frequency, and wide bandwidth data transmission systems to carry signals with 16 GHz total bandwidth from each antenna, and a new digital correlator with the capability to process this bandwidth with an unprecedented number of frequency channels for an imaging array. Also included are a new monitor and control system and new software that will provide telescope ease of use. Scheduled for completion in 2012, the EVLA will provide the world research community with a flexible, powerful, general-purpose telescope to address current and future astronomical issues.Comment: Added journal reference: published in Proceedings of the IEEE, Special Issue on Advances in Radio Astronomy, August 2009, vol. 97, No. 8, 1448-1462 Six figures, one tabl

Quantization Noise Shaping for Information Maximizing ADCs

ADCs sit at the interface of the analog and digital worlds and fundamentally determine what information is available in the digital domain for processing. This paper shows that a configurable ADC can be designed for signals with non constant information as a function of frequency such that within a fixed power budget the ADC maximizes the information in the converted signal by frequency shaping the quantization noise. Quantization noise shaping can be realized via loop filter design for a single channel delta sigma ADC and extended to common time and frequency interleaved multi channel structures. Results are presented for example wireline and wireless style channels.Comment: 4 pages, 6 figure

ULTRA-WIDEBAND NONLINEAR ECHO-CANCELLATION

Hybrid fiber coaxial (HFC) networks are used around the world to distribute cable television and broadband internet services to customers. These networks are governed by the Data-Over-Cable Service Interface Specification (DOCSIS) family of standards, with the most recent version at the time of this writing being DOCSIS 3.1. A frequency division duplex (FDD) spectrum is used in DOCSIS 3.1, where the upstream and downstream signals are separated in frequency to eliminate interference. A possible method to increase signal bandwidths is to use a full-duplex (FDX) spectrum, in which the US and DS signals use the same frequencies at the same time. A main challenge faced when implementing FDX in a DOCSIS node is eliminating the interference in the received US signal caused by the transmitted DS signal. One possible method for eliminating the interference is utilizing an echo-canceling algorithm, which predicts the self-interference (SI) based on the known DS signal and cancels it from the received US signal. Although echo-cancellation algorithms exist for fundamentally similar applications, the DOCSIS FDX case is more complicated for two main reasons. First, the DOCSIS node uses a nonlinear power amplifier to amplify the DS signal. Second, the DS signal is an ultra-wideband signal spanning a frequency range of up to 1.2 GHz. Most of the amplifier modeling techniques discussed in the literature were designed for narrowband wireless signals and will have limited performance when used with ultra-wideband signals. This thesis develops an algorithm to characterize the power amplifier and to predict the harmonics it generates for a given DS signal. These predicted harmonics can be used to cancel the SI signal in a full duplex DOCSIS system. The algorithm, which is referred to as the ultra-wideband memory polynomial (UWB-MP) model, is based on the well-known memory polynomial model with adaptations which allow the model to predict harmonics for ultra-wideband signals. Since a direct implementation of the UWB-MP model in an FPGA would result in very high resource usage, system architecture recommendations are provided. Our proposed implementation of the model compensates for harmonics up to and including the 3rd order, which has a power spectrum extending above 3600 MHz. Using the techniques discussed in this thesis, it is shown that a sampling rate of 4 GHz allows for cancellation of the SI signal while providing a reasonable balance between performance and resource usage. Matlab simulations of a DOCSIS node with various parameters and PA simulation models were conducted. The simulations showed that over 75 dB of cancellation of the SI signal is possible in an idealized hardware setup. It is also demonstrated that AWGN injected into the received signal does not reduce the ability of the model to estimate the PA harmonics, although the noise itself cannot be canceled. Further simulations showed that the UWB-MP model could cancel harmonics whose power is much higher than that specified in DOCSIS. Although the UWB-MP model was designed with memory polynomial type PAs in mind, simulation results show that significant cancellation is possible with PAs that are represented by Wiener models as well. Based on the simulation results, we recommend using a filter of length 20 coefficients for each harmonic in the UWB-MP model, and 60 iterations with 500 samples for estimating the coefficients with the least squares method

From Theory to Practice: Sub-Nyquist Sampling of Sparse Wideband Analog Signals

Conventional sub-Nyquist sampling methods for analog signals exploit prior information about the spectral support. In this paper, we consider the challenging problem of blind sub-Nyquist sampling of multiband signals, whose unknown frequency support occupies only a small portion of a wide spectrum. Our primary design goals are efficient hardware implementation and low computational load on the supporting digital processing. We propose a system, named the modulated wideband converter, which first multiplies the analog signal by a bank of periodic waveforms. The product is then lowpass filtered and sampled uniformly at a low rate, which is orders of magnitude smaller than Nyquist. Perfect recovery from the proposed samples is achieved under certain necessary and sufficient conditions. We also develop a digital architecture, which allows either reconstruction of the analog input, or processing of any band of interest at a low rate, that is, without interpolating to the high Nyquist rate. Numerical simulations demonstrate many engineering aspects: robustness to noise and mismodeling, potential hardware simplifications, realtime performance for signals with time-varying support and stability to quantization effects. We compare our system with two previous approaches: periodic nonuniform sampling, which is bandwidth limited by existing hardware devices, and the random demodulator, which is restricted to discrete multitone signals and has a high computational load. In the broader context of Nyquist sampling, our scheme has the potential to break through the bandwidth barrier of state-of-the-art analog conversion technologies such as interleaved converters.Comment: 17 pages, 12 figures, to appear in IEEE Journal of Selected Topics in Signal Processing, the special issue on Compressed Sensin

Development and Experimental Analysis of Wireless High Accuracy Ultra-Wideband Localization Systems for Indoor Medical Applications

This dissertation addresses several interesting and relevant problems in the field of wireless technologies applied to medical applications and specifically problems related to ultra-wideband high accuracy localization for use in the operating room. This research is cross disciplinary in nature and fundamentally builds upon microwave engineering, software engineering, systems engineering, and biomedical engineering. A good portion of this work has been published in peer reviewed microwave engineering and biomedical engineering conferences and journals. Wireless technologies in medicine are discussed with focus on ultra-wideband positioning in orthopedic surgical navigation. Characterization of the operating room as a medium for ultra-wideband signal transmission helps define system design requirements. A discussion of the first generation positioning system provides a context for understanding the overall system architecture of the second generation ultra-wideband positioning system outlined in this dissertation. A system-level simulation framework provides a method for rapid prototyping of ultra-wideband positioning systems which takes into account all facets of the system (analog, digital, channel, experimental setup). This provides a robust framework for optimizing overall system design in realistic propagation environments. A practical approach is taken to outline the development of the second generation ultra-wideband positioning system which includes an integrated tag design and real-time dynamic tracking of multiple tags. The tag and receiver designs are outlined as well as receiver-side digital signal processing, system-level design support for multi-tag tracking, and potential error sources observed in dynamic experiments including phase center error, clock jitter and drift, and geometric position dilution of precision. An experimental analysis of the multi-tag positioning system provides insight into overall system performance including the main sources of error. A five base station experiment shows the potential of redundant base stations in improving overall dynamic accuracy. Finally, the system performance in low signal-to-noise ratio and non-line-of-sight environments is analyzed by focusing on receiver-side digitally-implemented ranging algorithms including leading-edge detection and peak detection. These technologies are aimed at use in next-generation medical systems with many applications including surgical navigation, wireless telemetry, medical asset tracking, and in vivo wireless sensors