RF Circuit linearity optimization using a general weak nonlinearity model

This paper focuses on optimizing the linearity in known RF circuits, by exploring the circuit design space that is usually available in today’s deep submicron CMOS technologies. Instead of using brute force numerical optimizers we apply a generalized weak nonlinearity model that only involves AC transfer functions to derive simple equations for obtaining design insights. The generalized weak nonlinearity model is applied to three known RF circuits: a cascode common source amplifier, a common gate LNA and a CMOS attenuator. It is shown that in deep submicron CMOS technologies the cascode transistor in both the common source amplifier and in the common gate amplifier significantly contributes IM3 distortion. Some design insights are presented for reducing the cascode transistor related distortion, among which moderate inversion biasing that improves IIP3 by 10 dB up to 5 GHz in a 90 nm CMOS process. For the attenuator, a wideband IM3 cancellation technique is introduced and demonstrated using simulations

Exploring the Use of Two Antennas for Crosscorrelation Spectrum Sensing

Abstract—Spectrum sensing is one of the key characteristics of a cognitive radio. Energy detection provides maximum flexibility by not relying on any prior knowledge, but suffers from an SNRwall due to noise uncertainty. Crosscorrelation of the outputs of two receiver paths is a technique to reduce the noise level of the total receiver, and hence improves the SNR. The reduction of the noise is limited by correlated noise originating from shared components near the antenna. In this paper we explore the use of a separate antenna for each receiver for crosscorrelation spectrum sensing. One immediate advantage is that due to the removal of the splitter, which was necessary to interface the single antenna to two receivers, the SNR improves, significantly reducing the required measurement time. A lot of the noise correlation can be removed, leading to a lower residual noise floor. The noise at each antenna will still be partially correlated due to mutual coupling, spatial noise correlation and man-made noise. We show that some signal power can be lost in the sensing process due to partial decorrelation of the signal at the two antennas. Fortunately, this seems to be a problem only in highly mobile environments, which makes the use of two-antenna crosscorrelation spectrum sensing an interesting solution towards more reliable energy detection

Using crosscorrelation to mitigate analog/RF impairments for integrated spectrum analyzers

An integrated spectrum analyzer is useful for built-in self-test purposes, software-defined radios, or dynamic spectrum access in cognitive radio. The analog/RF performance is impaired by a number of factors, including thermal noise, phase noise, and nonlinearity. In this paper, we present an integrated circuit with two integrated RF-frontends, of which the outputs are crosscorrelated in digital baseband. We show by theory and measurements that the above-mentioned impairments are mitigated by this technique. The presented 65-nm CMOS prototype operates at 1.2 V, and obtains a noise floor below 169 dBm/Hz, an of 25 dBm, and more than 20 dB of phase-noise reduction. In a special high-impedance mode, an even lower noise floor below 172 dBm/Hz is obtained

CMOS RF Transceiver considerations for Dynamic Spectrum Access

Cognitive Radio (CR), and in particular dynamic spectrum access (DSA), promises a much more efficient use of the spectrum by opportunistically using available frequencies. This asks for specific functionality, like spectrum sensing and frequency-agile transmission and reception. We will show that this functionality poses challenging hardware requirements, which go far beyond what is currently possible with an analogue-to-digital converter (ADC) and digital-to-analogue converter (DAC). Instead, a transceiver (transmitter+receiver) with filtering and frequency conversion is required. By starting from a mathematical abstraction for the description of transceivers and an overview on transceiver implementation, we will show that the flexibility required by CR calls for changes in the architecture, putting severe constraints on linearity and spurious emission performance. We will discuss several existing and proposed solutions to alleviate the design of CR transceivers and spectrum sensing functionality, with a special emphasis on CMOS as it is low-cost and enables the integration of both analogue and digital on one integrated circuit (IC). ****

Closed-form expressions for time-frequency operations involving Hermite functions

The product, convolution, correlation, Wigner distribution function (WDF) and ambiguity function (AF) of two Hermite functions of arbitrary order n and m are derived and expressed as a bounded, weighted sum of n+m Hermite functions. It was already known that these mathematical operations performed on Gaussians (Hermite functions of the zeroth-order) lead to a result which can be expressed as a Gaussian function again. We generalize this reciprocity to Hermite functions of arbitrary order. The product, convolution, correlation, WDF, and AF operations performed on two Hermite functions of arbitrary order lead to remarkably similar closed-form expressions, where the difference between the operations is primarily determined by distinct phase changes of the weights of the Hermite functions in the result. The closed-form expressions are generalized to the class of square-integrable functions. A key insight from the closed-form expressions is applied to the design of orthogonal, time-frequency localized communication signals which are characterized by an AF with rotational symmetry. In addition to this application, the theoretical expressions may prove useful for signal analysis in fields ranging from communications, radar and image processing to quantum mechanics

A CMOS-Compatible Spectrum Analyzer for Cognitive Radio Exploiting Crosscorrelation to Improve Linearity and Noise Performance

Abstract—A spectrum analyzer requires a high linearity to handle strong signals, and at the same time a low NF to enable detection of much weaker signals. This is not only important for lab equipment, but also for the spectrum sensing part of cognitive radio, where low cost and integration is at a premium. Often there is a trade-off between linearity and noise: improving one degrades the other. Crosscorrelation can break this tradeoff by reducing noise at the expense of measurement time. An existing RF frontend in CMOS-technology with IIP3=+11dBm and NF=5.5 dB is duplicated and attenuators are put in front to increase linearity to IIP3=+24 dBm. The attenuation degrades NF, but by using crosscorrelation of the outputs of the two frontends, the effective NF is reduced to around 5 dB. In total, this results in a spurious-free dynamic range of 88 dB in 1MHz resolution bandwidth