RFIC, mm-wave CMOS, microsensors

Millimeter-wave radars offer a practical solution to distinguish objects made of different materials, shapes, and compositions. In this work, radar classification of various materials is demonstrated using a broadband millimeter-wave CMOS integrated receiver. The receiver is used to record the transmitted power through multiple solid materials at various distances from the receiver in the W-band (75-110 GHz). Three supervised machine learning tools are trained by the recorded data to classify these materials into different categories. The trained classifiers were used to predict material and thickness of objects with varying distances from the receiver with accuracy levels of higher than 96% in material classification and 88% in thickness classification.

The impractical association of a dedicated fiber optic backhauling link with each base station in future wireless area network (WAN) networks promoted self-backhauling to become one of the most practical techniques for ultra-dense deployments. Selfbackhauling reduces the number of stations with fiber-optic links, while the remaining stations can communicate with the core network through wireless multi-hoping connections. Nevertheless, routing through self-backhauling stations is an NP-hard problem. In this study, we propose a routing scheme based on a semi-distributed self-learning algorithm to reduce the end-to-end latency which achieve better stability against the dynamic nature of the mobile network, such as load variations and link failures. The proposed solution offers changing propagation medium between freespace optical (FSO) and radio frequency (RF); this dynamic change between every two hops reduces power consumption, increases throughput, and minimizes latency. Based on the performed simulation, our proposed algorithm measured better overall bit error rate (BER) compared to both RF-only and free-space optical FSO-only techniques resulting in increased backhauling capacity and reduced overall route interference. This is an open access article under the CC BY-SA license.

— A bidirectional image selection transceiver is presented that operates over 71-76 GHz and 81-86 GHz with only 3 GHz of LO tuning range. A sliding-IF architecture with bidirectional VGAs allows operation in transmit and receive modes. The sliding IF and narrow LO tuning range allow wideband image rejection using a single stage polyphase filter. The circuit is implemented in a 90-nm SiGe BiCMOS process. Measurements indicate conversion gain of-2.5 dB to 3 dB with less than ±0.75 dB variation over 10 GHz in TX mode and-4dB to 0 dB with less than ±1 dB variation over 10 GHz bandwidth in RX mode. With 16-and 64-QAM, the EVM is below 5% and 4% at data rates of 6 Gb/s and 9 Gb/s. The RF and LO circuitry consumes at most 150 mW and 250 mW.

In this paper, a miniaturized front-end six-port
receiver prototyped by 130 nm CMOS technology at 60 GHz
frequency band is presented. The proposed six-port circuit
consists of three compact 3dB branch-line couplers (BLC) and
one compact Wilkinson power divider (WPD). Two
miniaturization techniques are used; meandering thin-film
microstrip transmission lines (MTFM) and capacitive loading
(CL). These two techniques lead to dramatic size reduction which
is desirable for MMIC technology. Moreover multi-level
metallization processes, offered for CMOS technology, is used.
The results are provided based on a full-wave commercial
electromagnetic package, ADS Agilent. The simulated results
show good impedance characteristics over 57-64 GHz frequency
band. The S-parameter results, as well as constellation diagram
of QPSK modulation with data rate of 3.52 Gbps for three
different cases confirm the capability of miniaturized six-port
circuit for high data-rate wireless personal area network
(WPAN) applications at 60 GHz frequency band.