Trial Program ENCOR-Phase 2 Enabling Methods for Dynamic Spectrum Access and Cognitive Radio 7 May 2014 Mikko Valkama, Visa Koivunen, Markku Renfors,Jussi Ryynänen mikko.e.valkama@tut.fi; visa.koivunen@aalto.fi ENCOR project scope overall, phases 1 and 2 Focus on concept design, signal processing methods and radio circuits in dynamic spectrum access and cognitive radio networks with strong demonstration emphasis. The goal of the project is to develop new HW f and algorithm solutions for cognitive radios and RF verify their functionality with test platform initiated by Nokia, and developed further in this project, in real radio environments. More detailed focus areas: Spectrum exploration and exploitation methods, focus on decentralized and collaborative methods as well as wideband sensing techniques Energy-efficient hardware implementations Modeling and mitigation of hardware originated interference and RF nonidealities Increasing the efficiency of spectrum sensor implementations with combined detectors Reconfigurable building blocks for receiver chain, including wideband multiband A/D interface and sensor linearization. Real-word field measurements and demonstrations
ENCOR phase 2 essentials Taking the developed methods and concepts into practical deployment level in example applications Deployment scenarios may cover both commercial as well military/private applications of dynamic spectrum access and cognitive radio communications. Implementing cooperative sensing and interference modeling and related fusion of the acquired information using spectrum sensor and cognitive radio platform, as well as hardware emulation based evaluation of dynamic spectrum access schemes in a heterogeneous radio environments Also continuing selected more research-oriented tasks Industrial and International cooperation Finnish industry (Broadcom, Nokia, Elektrobit) and Finnish Defence Forces International universities (Princeton, UCLA, UC Berkeley, TU Ilmenau) More than 20 person months of researcher exchange in 2013-2014! ENCOR-2 International Collaboration Examples of long-term researcher exchange UCLA, USA; Ali Shahed Host: Prof. Danijela Cabric Topics: ultrawideband spectrum sensor and wideband spectrum sensor linearization Duration: 11/2011-9/2013 Princeton University, USA; Visa Koivunen Host: Prof. Vincent Poor Topics: collaborative spectrum exploration and exploitation Duration: 9/2013-6/2014 Berkeley BWRC, USA; Marko Kosunen Host: Prof. Borivoje Nikolic Topics: cognitive radio transmitter architectures, sensor HW Duration: 9/2013-4/2014 Also many other shorter (1-2 months) visits
Some general thoughts.. Increasing the flexibility and efficiency in RF spectrum use is a general trend and challenging target in all emerging wireless communications Many developments in ENCOR/ENCOR2, related to e.g. wideband receivers and receiver linearization serve this purpose in broad sense Spectrum sensing and dynamic exploitation, in turn, is now strongly on table through e.g. LTE Unlicenced (LTE-U) Pushed strongly by e.g. Qualcomm Prevailing rules on how to behave at ISM bands call for additional coexistence methods (beyond normal CSMA/CA) to e.g. protect WiFi Some kind of sensing at enb side likely to place Furthermore, Internet-of-Things (IoT) can eventually be understood/utilized as a big interconnected sensor network Some general thoughts.. Some of the device technologies developed in ENCOR/ENCOR2, mostly for wideband sensing receivers, have already found applications also in commercial mobile cellular systems E.g. extremely wideband multi-radio multi-operator basestation transceivers with 100MHz or 200MHz instantaneous BW..and noncontiguous carrier aggregation UE receiver with single RF chain is another good example This would not have been possible without TRIAL programme Sensor platform and field measurement environment developments will also continue
Result Snap-shots In the following, some example outcomes are high-lighted, stemming from national and international cooperation within ENCOR/ENCOR2 That is then followed by collaborative spectrum sensor field measurements (separate slides by Marko Kosunen) The following is only a snapshot of the overall work from one angle, namely receiver linearity challenges Susbtantial work in other areas as well, e.g. collaborative sensing and exploitation algorithms Device Technologies for Very Wideband Spectrum Sensing - Overview of Analog-FFT based Sensing Receiver with up to 500MHz Instantaneous Bandwidth UCLA based collaboration activity
High-level structure Wideband RF S/P IDEAL FFT TWIDDLE FACTOR ERROR SHARING ERROR AGC AGC AGC AGC A/D A/D A/D A/D AFFT Compensation Classification Engine 9 Targets and technology Analog design (40 nm CMOS) - Charge based Analog FFT (AFFT) using passive switched cap filters - Elementary coarse channelization, 8 bins, reduced ADC specifications Digital baseband (40 nm CMOS, Digital ASIC) - Identification and classification of non-overlapping and overlapping signals in 5, 50 and/or 500 MHz channels. - Minimum signal bandwidth: 12.5 KHz for 5 and 50 MHz mode and 200 KHz for 500 MHz mode. - Band segmentation utilizing Digital FFT - Modulation classification: hierarchical approach (mod class + overlapping signals) - Implementation: low power DSP methodology & programmable FFT architecture RF-frontend (off-the-shelf components) -Supports 5, 50 and 500MHz channels for 400MHz. 6GHz 10
Big Picture Digital Chip 0.50 mm Universal DSP 7.1 mw 1.26 mm Classifier 10.2 mw partial PSD (35.4 mw full PSD) Band Segmentation Processor 1.15 mm 0.39 mm Measured performance Technology 1P10M 40nm Logic I/O I:47 &O:25 Logic V DD 0.35~0.9 V Mem. V DD 0.55~0.9 V Core Area 1.6 1.8 mm 2 Gate Count Throughput Peak Effi. (GOPS/mW) Energy per classification [µj] 4.15 M 500 MS/s 5.1 (BSeg.) 5.6 (Class.) 17 5MHz 44 50MHz 32 500MHz Fully functional digital chip Energy per classification < 44 µj 12
DSP Algorithm Innovations for Suppressing RF Impairments in Sensing Receivers - Tailored linearization solutions for wideband perchannel sensing receivers Joint work with UCLA and Aalto Characterization and DSP-based Enhancement of Nonlinear Sensing RX s In collaboration with UCLA Addressing the nonlinear distortion aspects in sensing receivers Intermodulation of strong signals hurt reliable identification of free spectrum Energy and feature detectors Quantifying this, in particular from modern feature detection perspective Developing DSP-enhanced sensor RX s
Characterization and DSP-based Enhancement of Nonlinear Sensing RX s Example with N=500 (sample size), RX IIP3 = -10dBm, 10MHz final sensing BW, 4dB NF, PU SNR = 10dB, RX input power approx. -20dBm Solid: analysis, markers: empirical Characterization and DSP-based Enhancement of Nonlinear Sensing RX s DSP enhanced receiver 1: deploy the analysis results, elementary RX IIP knowledge and blocker power estimation to adapt your sensing calculations (sensing time and threshold)
Characterization and DSP-based Enhancement of Nonlinear Sensing RX s Example with fixed Pfa = 0.1, RX IIP3 = -10dBm, 10MHz final sensing BW, 4dB NF, PU SNR = 3dB, RX input power approx. -23dBm Can buy back the performance through somewhat increased sensing time Characterization and DSP-based Enhancement of Nonlinear Sensing RX s DSP enhanced receiver 2: deploy the analysis results and adaptive digital intermodulation cancellation to enhance the observation prior to sensing calculations
Characterization and DSP-based Enhancement of Nonlinear Sensing RX s Example with fixed N=500 (sample size), Pfa = 0.1, RX IIP3 = -10dBm, 10MHz final sensing BW, 4dB NF, PU SNR = 3dB, RX input power varying for approx. -15dBm -40dBm Characterization and DSP-based Enhancement of Nonlinear Sensing RX s Reduced complexity processing also developed for special case of neighboring channel leakage due to sensing RX nonlinearity
Characterization and DSP-based Enhancement of Nonlinear Sensing RX s Example measured performance with ENCOR sensor board and developed DSP processing for 8MHz DVB type channel with high power neighboring signals DSP Algorithm Innovations for Suppressing Nonlinear Distortion in Wideband Radio Receivers - Modeling and Suppression of Complete Receiver Chain Nonlinearities in Wideband Receivers
Wideband RX linearization including RF and BB nonlinearities Radio receivers have multiple cascaded nonlinearity sources (LNA, mixers, baseband amplifiers, ) Usually nonlinearity modeling is focusing on RF or baseband only, lacking the joint effects In addition, different nonlinearity profiles on RF and baseband Modeling and suppression of complete chain of nonlinearities in wideband RX PSD in dbm/hz -20-40 -60-80 -100-120 -140 Y distorted Y original mitigated LS solution -10-5 0 5 10 Frequency in MHz Wideband RX linearization including RF and BB nonlinearities In collaboration with TU Ilmenau, Germany Complete modeling through elementary LNA, mixer and BB amplifier models
Wideband RX linearization including RF and BB nonlinearities Digital linearization concept developed to suppress all essential nonlinear distortion from the wideband spectrum perspective Stemming from the previous modeling, learns the nonlinear distortion characteristics withojt prior knowledge Wideband RX linearization including RF and BB nonlinearities Enhanced further to parallel processing form Reduced complexity and better identification properties
Wideband RX linearization including RF and BB nonlinearities Simulated two-tone example Wideband RX linearization including RF and BB nonlinearities Simulated multicarrier waveform example
Wideband RX linearization including RF and BB nonlinearities Measured two-tone test Example Papers in this area M. Grimm, M. Allén, J. Marttila, M. Valkama, and R. Thomä, Joint mitigation of nonlinear RF and Baseband distortions in wideband directconversion receivers, IEEE Trans. Microwave Theory and Techniques, vol. 62, no. 1, pp. 166-182, Jan. 2014. E. Rebeiz, A. Shahed hagh ghadam, M. Valkama, and D. Cabric, Spectrum sensing under RF non-linearities: Performance analysis and DSP-enhanced receivers, submitted to IEEE Trans. Signal Processing. E. Rebeiz, A. Shahed hagh ghadam, M. Valkama, and D. Cabric, "Suppressing RF front-end nonlinearities in wideband spectrum sensing," in Proc. International Conference on Cognitive Radio Oriented Wireless Networks (CrownCom 2013), Washington D.C., July 2013. M. Allén, J. Marttila, M. Valkama, S. Mäkinen, M. Kosunen, and J. Ryynänen, Digital linearization of direct-conversion spectrum sensing receiver, in Proc. IEEE Global Conf. on Signal and Information Processing (GlobalSIP 2013), Austin, TX, Dec. 2013.
Scientific articles and thesis works already in ENCOR phase 1 12 journal articles 31 conference articles 4 MSc theses Big contributions to 4 PhD theses..marko will continue next (separate slides) with sensor field measurements