Presentation on theme: "1 Dirty RF Impact on Interference Alignment Per Zetterberg."— Presentation transcript:
1 Dirty RF Impact on Interference Alignment Per Zetterberg
2 Outline Goal Approach Interference-alignment and CoMP Implementation Results Impairment-modeling (closening the gap theory-simulation) Conclusion
3 Goal Testbed Measurements (USRP) Impairment- modeling FER EVM SINR Match! Detailed simulation New interesting and challenging techniques Assumption: Results are general. Channels Robust approaches
4 Approach Transmitter Spectrum analyzer Test-bed Measurements (USRP) Impairment- modeling Basic simulation PC Impairment model
5 Interference alignment K-transmitters and K-receivers, K-links: K/2 simultaneous interference-free links. Requires coding over multiple channel realizations. Global channel knowledge required. Cadambe/Jafar, ”Interference Alignment and Degrees of Freedom of the K-User Interference Channel”, IEEE Trans, Information Theory 2008.
6 Interference-alignment incarnations In frequency-domain: Something new –will be studied later. In antenna-domain: Co-ordinated beam-forming.
7 Co-ordinated Multi-Point CoMP
8 Implementation IA BS 1 BS 2 BS 3 MS 1 MS 2 MS 3 Feedback: Wired ethernet
9 Implementation: CoMP BS 1 BS 2 BS 3 MS 1 MS 2 MS 3 Feedback: Wired ethernet
10 Beamformer “Approaching the Capacity of Wireless Networks through Distributed Interference Alignment", by Krishna Gomadam, Viveck R. Cadambe and Syed A. Jafar. Formulate virtual uplink SINR. Iterate
14 Power-Amplifier Non-linearity OFDM signals: + Modeled as noise: D Dardari, V. Tralli, A Vaccari “A theoretical characterization of nonlinear distortion effects in OFDM systems“, IEEE Trans. Comm., Oct 2000.
15 MIMO case OFDM signals: + + Correlation ?
16 Phase-noise A/DLPFBPFLNA Modeled as additive noise + CPE CPE: Slowly varying between symbols R. Corvaja, E. Costa, and S. Pupolin, “M-QAM-OFDM system performance in the presence of a nonlinear amplifier and phase noise, IEEE Trans. Comm
17 CoMP Results Without impairment model With impairment model
18 IA Results Without impairment model With impairment model
19 Conclusion: What will be answered? How much worse is IA practice than in theory? What practical impairments need to be modeled? (==> can lead to improved robust designs) Is IA still worthwhile with impairments compared to base-lines ? Other outputs Software environments that can be re-used (commodity hardware) Increased understanding of software and hardware issues and implementations in our research community and our PhDs in particular. Course-work for the above.
20 Structure of model TX RX TX RX Channel TX- impairment
21 Our Hardware PC Linux Gbit-Ethernet USRP N210 Sample-rate: 100MHz Streaming: 25MHz We have 18 USRPs GPS PPS, 10MHz
22 The 4Multi Software FrameWork (Multi-Antenna, Multi-User, Multi-Cell, Multi-Band) Send data in small bursts (relaxes computational load) Nodes synchronized by external trigering (PPS) The implementor (basically) only need to program three functions node::init, node::process and node::end_of_run. Simulate the system using “simulate” generic function. Everything that can be compiled with gcc can run (e.g IT++) Toolbox with coding&modulation. Store _all_ received signals for post-processing. Vision: “The coding should be as easy as performing ordinary (but detailed) desktop simulations”