RF spectrum sensing in CMOS exploiting crosscorrelation

The introduction of new wireless services, the demand for higher datarates,\ud and higher traffic volumes call for a more efficient use of the RF spectrum\ud than what is currently possible with static frequency allocation. Dynamic\ud spectrum access offers a more efficient use by allowing unlicensed users to\ud opportunistically use locally and temporarily unoccupied licensed bands\ud (‘white space’).\ud To prevent harmful interference to the licensed users, unlicensed users\ud need tomake sure the band is free before they are allowed to transmit. This\ud means that, if resorting to databases is not possible or desired, the unlicensed\ud users have to be able to detect very weak signals from the licensed\ud users by means of spectrum sensing. Different types of spectrum sensing\ud exist, but it is preferable to use one that does not require knowledge of the\ud signals to be detected, as it can then be employed in arbitrary frequency\ud bands. Such a solution is energy detection (ED). The first step of ED is\ud similar to what a spectrum analyzer (SA) does: measure the power in a\ud frequency band. The second step is to distinguish between measuring\ud only noise, or noise plus a signal. Due to inaccuracies in the noise level\ud estimation, there is a certain minimum signal-to-noise ratio (SNR), the\ud SNR-wall, below which signals cannot be reliably detected. Several analog\ud impairments, such as phase noise, nonlinearity, and limited harmonic rejection\ud (HR), can also hamper the detection process by causing false alarms\ud or missed detections.\ud To reduce the SNR-wall and the influence of analog impairments on\ud sensing performance, crosscorrelation (XC) spectrum sensing, as a generalization\ud of autocorrelation (AC) (the standard form of ED), is proposed. XC\ud multiplies and integrates the outputs of two receivers, each processing the\ud same signal, to obtain the signal power, while the noise (ideally) averages\ud out. The noise uncertainty is removed at the cost ofmeasurement time, and\ud the SNR-wall reduces. A mathematical model is developed that predicts\ud that (1) a lower noise correlation between the two receivers lowers the\ud SNR-wall, and (2) resistive attenuation at the input of each receiver does\ud not influence the sensitivity of XC. This allows a design to be optimized for\ud high linearity without affecting the detection capabilities. By employing\ud a separate oscillator for each receiver, XC can also reduce phase noise. A\ud frequency offset between the two oscillators, in combination with some\ud digital signal processing, also allows XC to improve HR.\ud A first mostly-discrete prototype is developed, employing a mixer-first\ud architecture for high linearity. It demonstrates (phase) noise reduction and\ud an attenuation-independent noise floor using XC, but suffers from external\ud frequency-dependent coupling between the receivers, crosstalk between\ud the mixers, and a poor HR. A second protype tackles these disadvantages\ud by integrating two RF-frontends into a single 1.2V 65nm CMOS-chip,\ud with a novel distortion-cancellation technique in the attenuators for high\ud linearity.\ud Measurements show that XC achieves 22 dB of phase noise reduction\ud (limited by measurement time), and up to 25 dB of improvement in HR\ud (limited by crosstalk). At 10 dB attenuation, the SNR-wall is found to be\ud -184 dBm/Hz, which is 10 dB below the thermal noise floor, and even\ud 12 dB below the measured SNR-wall of AC. XC achieves an attenuationindependent\ud noise floor < -169 dBm/Hz from 0.3–1.0 GHz, with an IIP3\ud of +25dBm at 10 dB attenuation, which makes the spurious-free dynamic\ud range higher than that of high-end commercial SAs. Furthermore, it is experimentally\ud shown that XC can be much faster and more energy-efficient\ud than AC.\ud Overall, XC is shown to enable the integration of SAs with high sensitivity,\ud good resilience to strong interferers, and with speed and, at low\ud SNR, energy consumption benefits compared to AC. This not only makes\ud sensitive spectrum sensing attainable in a hostile radio environment, but\ud also paves the way for low-cost, low-power, and high-quality (mobile)\ud measurement equipment. Furthermore, it may enable the integration of\ud (many) small SAs inside other chips for built-in self-test (BIST), reducing\ud on pin count and test time during manufacturing, as well as more reliable\ud and stable performance during operation

Guest Editorial 2020 Custom Integrated Circuits Conference

THIS Special Issue of the IEEE JOURNAL OF SOLIDSTATE CIRCUITS features expanded versions of key articles presented at the 2020 Custom Integrated Circuits Conference (CICC), one of IEEE’s first conferences to go fully virtual due to the corona virus pandemic, from March 22 to March 25, 2020. Originally planned to be held at Hyatt Boston Harbor, Boston, MA, USA, growing concerns related to COVID-19 and the impact on the community’s ability to travel to the conference lead the conference organization to make the tough decision in January 2020 to go for a fully virtual format

A cross-correlation sub-sampling receiver for low power applications in a low SINR environment

Wireless sensor networks have recently emerged in a wide range of applications. Many attributes are essential for such networks such as: low cost, small form-factor, limited peak power consumption and the ability to operate in harsh interference scenarios. Most of these networks do not require high data-rates to operate. In this respect, sub-sampling receivers have shown promising results but suffer from noise folding and interference aliasing. In this paper, a sub-sampling receiver in combination with cross-correlation is used to enhance sensitivity and interference robustness while maintaining the sub-sampling advantages. An architecture which uses two different sampling frequencies is proposed. It shows ∼2dB SNR improvement compared to traditional architectures due to cross-correlation and an additional ∼2dB for each doubling of integrations. For a BER of 10– 3 , the required SIR is reduced with 4.5dB, 11.5dB and 14.5dB after using cross-correlation with the same, half and quarter data-rate used respectively. These improvements allow for a lower-power and lower-cost implementation