Name
Abstract | ||
|---|---|---|
With continuous exploitation of sub-6GHz wireless communication standards and the advent of 5G and 6G, the demand for faster speed and wider coverage keeps evolving. While it is expected to utilize higher working frequency to provide larger bandwidth, lower noise Figure (NF) is also preferred to achieve better sensitivity or wider coverage. A straightforward solution to achieve a low NF is to employ LNA-first architecture; this configuration helps to achieve a sub-2dB NF for frequencies up to 6GHz. However, the Gm-cell does consume extra power [1], [2]. Meanwhile, noise cancellation techniques are widely used to improve the noise performance [3] –[5]. Nevertheless, due to the input parasitic capacitance, the common-source/mixer-first hybrid architecture cannot guarantee a low NF for frequencies above 3GHz [3]. The 1.8dB-NF 5GHz receiver eliminates the noise contribution of its input series inductor but requires a large power consumption $(\sim 100$ mW) [4]. Similar power consumption is needed for the frequency-translational quadrature-hybrid receiver [5]. |
Year | DOI | Venue |
|---|---|---|
2021 | 10.1109/ISSCC42613.2021.9365954 | 2021 IEEE International Solid- State Circuits Conference (ISSCC) |
Keywords | DocType | Volume |
communication standards,LNA-first architecture,noise cancellation techniques,noise performance,frequency translational quadrature-hybrid receiver,transformer-based noise-cancelling CMOS receiver front-end,wireless communication standards,noise figure,input parasitic capacitance,mixer-first hybrid architecture,power consumption,frequency 5.0 GHz,noise figure 1.75 dB,noise figure 1.8 dB | Conference | 64 |
ISSN | ISBN | Citations |
0193-6530 | 978-1-7281-9550-6 | 0 |
PageRank | References | Authors |
0.34 | 0 | 10 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Kaituo Yang | 1 | 3 | 2.82 |
| Chirn Chye Boon | 2 | 136 | 26.81 |
| Guangyin Feng | 3 | 5 | 5.56 |
| Chenyang Li | 4 | 3 | 1.46 |
| Zhe Liu | 5 | 62 | 15.62 |
| Guo Ting | 6 | 4 | 4.25 |
| Xiang Yi | 7 | 31 | 6.61 |
| Yangtao Dong | 8 | 0 | 2.03 |
| Ao Zhou | 9 | 0 | 0.68 |
| Xiaoying Wang | 10 | 14 | 18.68 |