A Single RF Channel Smart Antenna Receiver Array with Digital Beamforming
Darren Goshi, Yuanxun (Ethan) Wang, Tatsuo Itoh
University of California, Los Angeles Electrical Engineering Dept. Los Angeles, CA
University of California, Los Angeles
Single RF Channel Smart Antenna System
LPF ADC
LNA Mixer LPF ADC Digital MUX DEMUX Beam- Former
LPF ADC
Antenna Single RF Array Channel IF/Baseband Processing
¾MUX reduces N-channels (LNAs, Mixers) to 1 ¾Flexibility in IF/baseband processing – analog or digital DEMUX ¾Digital Beamforming in MATLAB environment
University of California, Los Angeles System Features
9 Reduction in costly RF hardware 9 Space reduction 9 Reduction in power dissipation 9 Maintains complete functionality as with typical smart antenna arrays
University of California, Los Angeles
Traditional DBF Smart Antenna System
LNAs Mixers
LPF ADC
LPF ADC Digital Signal Processing / Beamforming
LPF ADC
¾N-channel array requires N individual receiver chains ¾Each channel must be well matched and calibrated
University of California, Los Angeles System Principles
Switching waveform
Г=1 (when switch is open)
¾SMILE (Spatial MultIplexing of Local Elements) scheme 9 Sequential switching samples signal at each element 9 Sampling rate greater than Nyquist rate 9 Parallel feed network retains all signal information 9 Sampling frequency limits signal modulation bandwidth
University of California, Los Angeles
System Principles
Sampling Frequency:
fBNs ≥×
LPF Cutoff Frequency: BB <<−ff 22lpf s
University of California, Los Angeles System Principles
0.5
0
-0.5 18 19 20 21 22 23 24 25 0.5 o 0 ¾Baseband data recovery
-0.5 18 19 20 21 22 23 24 25 0.5
0 9 Non-conventional feed Array at 0 -0.5 18 19 20 21 22 23 24 25 0.5 network properly retains 0
-0.5 18 19 20 21 22 23 24 25 time µs phase information 0.5
0
-0.5 9 Allows use of advanced 18 19 20 21 22 23 24 25 0.5 o 0 beamforming and DOA -0.5 18 19 20 21 22 23 24 25 0.5
0
Array at 30 Array algorithms -0.5 18 19 20 21 22 23 24 25 0.5
0
-0.5 18 19 20 21 22 23 24 25 time µs
University of California, Los Angeles
4-Element Prototype Hardware
¾LNA MUX 9 NEC32485C 4-Element Antenna Array Pseudomorphic HJ FET (LNAs) as switching element MUX 9 Low-noise switching improves overall noise figure Feed Network with compared with passive Single RF Output switch 9 No current required to LNA MUX with patch drive switching antenna element at 5.8 GHz
University of California, Los Angeles Non-conventional Feed Network
Non-conventional array feed network
¾Always Matched Feed Network 9 Only one active channel at each instant 9 All lines at T-junction matched to Zo 9 No loss compared with 6 dB loss of Wilkinson dividers
University of California, Los Angeles
Circuit Schematic
From Antenna
Gate Bias LNA ¾Multiplexing Hardware Circuit NE32485C HJFET 9 Tank circuit adds isolation
sacrificed with non-conventional Tank Circuit feed network
9 Switch reference must be l λ/2 precisely matched to feed network Switch Zo Reference 3λ/2 Γ≈1 when off Zo
Z o To Single RF Channel
University of California, Los Angeles Single Source Testbed Setup
Antenna chamber SMILE array
LNA Horn antenna LO RF Gen
Digital PC Data oscilloscope acquisition
University of California, Los Angeles
Two Source Testbed Setup
RF Gen RF Gen
Horn antenna Horn antenna
SNOI SOI
SMILE array LNA
LO
Digital PC Data oscilloscope acquisition
University of California, Los Angeles Beamforming Performance
Synthesized Beam Patterns ¾Digital Beamforming 9 Synthesized beamforming LNA MUX Switching accomplished in DSP 0 0 -40 40 ¾FET Switching Benefits -5 9 Fast switching with FET -10 increases possible data rate
Amplitude [dB] Amplitude -15 9 Broader Symmetric Scan
-20 Range
-25 9 Lower sidelobes -80 -70 -60 -50 -40 -30 -20 -10 0 10 20 30 40 50 60 70 80 Theta [deg]
University of California, Los Angeles
Digital Data Recovery
Demodulated Data 0.3
0.2
0.1
0
-0.1
-0.2
0 1 2 3 4 5 6 7 8 9 10
After Digital Beamforming
0.2
0.1
0
-0.1
-0.2
0 1 2 3 4 5 6 7 8 9 10 Time µs 200 kbps 600 kbps 1 Mbps
¾Digital Data
9 BPSK modulated carrier 9 Compare demodulation before and after applying DBF 9 Digital beamforming algorithm coherently sums all channels
University of California, Los Angeles DOA Estimation and Synthesized Patterns
Single Source 0 Synthesized Pattern DOA estimation
-5 ¾DOA Estimation
-10 9 Proper recovery of IF channel data
-15 allows advanced beamforming
-20 algorithms and DOA estimation
-25 9 MUSIC algorithm detects proper -100 -80 -60 -40 -20 0 20 40 60 80 100 Angle Two Sources direction of signals 0 ¾Synthesized Beamforming -5
-10 9 Beam formed indirection of source
-15 9 Null formed in direction of unwanted
-20 signal
-25
Synthesized Pattern DOA estimation -30 -100 -80 -60 -40 -20 0 20 40 60 80 100 Angle
University of California, Los Angeles
Spatial Filtering
Before Digital Beamforming 0.3
Single Source: 0.2
0.1
0
-0.1
-0.2
-0.3 0 5 10 15 20 25 30 35 40 45 50
After Digital Beamforming 0.3
0.2
0.1
0
-0.1
-0.2
-0.3 0 5 10 15 20 25 30 35 40 45 50 Time, us ¾Single Source Data Recovery
9 Coherent summation recovers a much clearer pattern 9 Results more evident for angles farther off broadside
University of California, Los Angeles Spatial Filtering
Before Digital Beamforming 0.3
Two Sources: 0.2
0.1
0
-0.1
-0.2
-0.3 0 5 10 15 20 25 30 35 40 45 50
After Digital Beamforming 0.3
0.2
0.1
0
-0.1
-0.2
-0.3 0 5 10 15 20 25 30 35 40 45 50 Time µs ¾Two Source Data Recovery
9 Incoherent demodulation does not resemble a digital pattern 9Interference ‘nulling’ demonstrates spatial filtering
University of California, Los Angeles
Conclusion
¾Measured 20 MHz switching rate ¾DOA Estimation and Beamforming ¾Recovered up to 1 Mbps digital data ¾Demonstrated full smart antenna functionality
University of California, Los Angeles Other Works
¾Slot Antenna Based SMILE Array 9 Compact design 9 Series fed PIN diode switching
¾2-D Configuration 9 Increase scanning flexibility for possible radar application
University of California, Los Angeles