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

Feedback Quantization in Crosscorrelation Predistorters

Amplification of signals with fluctuating envelopes inevitably leads to distortion because of nonlinear behavior of the power amplifier (PA). Digital predistortion can counteract these nonlinear effects. In this letter, the crosscorrelation predistorter is described and the effects of quantization in the feedback path are presented. One of the effects is that the quantization noise is correlated with the signal to be quantized, resulting in reduced performance of predistortion. A technique to reduce these effects is to inject a dither signal before quantization. Because of the quantization noise and dither signal, more data has to be used to obtain estimates of the PA behavior that are accurate enough for effective predistortion

CORRELATION PROPERTIES OF QUANTIZATION NOISE

This paper examines the correlation properties of quantization noise. The quantization noise energy is subtractive if the quantizer output levels are optimized for the probability density of the input signal (pdf optimized). This paper gives a new result that shows that a quantizer (uniform or not) which has quantizer break points midway between output levels (a minimum distance quantizer) and is scaled to minimize the mean-square error, also has this property. Examples are shown that show the correlation properties which determine whether the quantization noise energy is subtractive or additive. This paper also considers a postfilter configuration that compensates for the quantization noise. The postfilter frequency domain gains take the correlation properties of the quantization noise into account. An experiment on reducing the effect of quantization noise in speech gives an indication that taking account of the correlation is useful. Index Terms — Quantizers, quantizer noise correlation 1

Fronthaul Quantization as Artificial Noise for Enhanced Secret Communication in C-RAN

This work considers the downlink of a cloud radio access network (C-RAN), in which a control unit (CU) encodes confidential messages, each of which is intended for a user equipment (UE) and is to be kept secret from all the other UEs. As per the C-RAN architecture, the encoded baseband signals are quantized and compressed prior to the transfer to distributed radio units (RUs) that are connected to the CU via finite-capacity fronthaul links. This work argues that the quantization noise introduced by fronthaul quantization can be leveraged to act as "artificial" noise in order to enhance the rates achievable under secrecy constraints. To this end, it is proposed to control the statistics of the quantization noise by applying multivariate, or joint, fronthaul quantization/compression at the CU across all outgoing fronthaul links. Assuming wiretap coding, the problem of jointly optimizing the precoding and multivariate compression strategies, along with the covariance matrices of artificial noise signals generated by RUs, is formulated with the goal of maximizing the weighted sum of achievable secrecy rates while satisfying per-RU fronthaul capacity and power constraints. After showing that the artificial noise covariance matrices can be set to zero without loss of optimaliy, an iterative optimization algorithm is derived based on the concave convex procedure (CCCP), and some numerical results are provided to highlight the advantages of leveraging quantization noise as artificial noise.Comment: to appear in Proc. IEEE SPAWC 201

Spectral Efficiency of One-Bit Sigma-Delta Massive MIMO

We examine the uplink spectral efficiency of a massive MIMO base station employing a one-bit Sigma-Delta ( \Sigma \Delta ) sampling scheme implemented in the spatial rather than the temporal domain. Using spatial rather than temporal oversampling, and feedback of the quantization error between adjacent antennas, the method shapes the spatial spectrum of the quantization noise away from an angular sector where the signals of interest are assumed to lie. It is shown that, while a direct Bussgang analysis of the \Sigma \Delta approach is not suitable, an alternative equivalent linear model can be formulated to facilitate an analysis of the system performance. The theoretical properties of the spatial quantization noise power spectrum are derived for the \Sigma \Delta array, as well as an expression for the spectral efficiency of maximum ratio combining (MRC). Simulations verify the theoretical results and illustrate the significant performance gains offered by the \Sigma \Delta approach for both MRC and zero-forcing receivers

A Novel Three-Point Modulation Technique for Fractional-N Frequency Synthesizer Applications

This paper presents a novel three-point modulation technique for fractional-N frequency synthesizer applications. Convention modulated fractional-N frequency synthesizers suffer from quantization noise, which degrades not only the phase noise performance but also the modulation quality. To solve this problem, this work proposes a three-point modulation technique, which not only cancels the quantization noise, but also markedly boosts the channel switching speed. Measurements reveal that the implemented 2.4 GHz fractional-N frequency synthesizer using three-point modulation can achieve a 2.5 Mbps GFSK data rate with an FSK error rate of only 1.4 %. The phase noise is approximately -98 dBc/Hz at a frequency offset of 100 kHz. The channel switching time is only 1.1 μs with a frequency step of 80 MHz. Comparing with conventional two-point modulation, the proposed three-point modulation greatly improves the FSK error rate, phase noise and channel switching time by about 10 %, 30 dB and 126 μs, respectively