[Discuss-gnuradio] PhD Position in Wireless Communication Systems
Apologies if you receive multiple copies of this posting?! There are openings for highly motivated and energetic MSc/PhD students to work in my research group. The ideal candidate must have a strong mathematical background, very good knowledge of wireless communication systems, and good software programming skill. Areas of research topics will includ, but not limited to, vehicle to everything (V2X) system, millimeter wave (massive MIMO) system, and intelligent (machine learning) techniques for wireless system design. Interested applicants can send me CV, transcript and other relevant documents all COMBINED in one PDF file to tebog...@ncat.edu or tadilo.bog...@gmail.com. More information about the position can be found in http://tadilo-bogale.com/ALLDocuments/Bogale-NCAT-Openings.pdf I would appreciate if you can share to potential candidates! Best Regards Tadilo Endeshaw Bogale - Tadilo Endeshaw Bogale, PhD Assistant Professor North Carolina A&T State University McNair Hall: 533 Greensboro, NC, USA E-mail : tebog...@ncat.edu<mailto:tebog...@ncat.edu> tadilo.bog...@gmail.com<mailto:tadilo.bog...@gmail.com> (private) Personal: http://tadilo-bogale.com<http://tadilo-bogale.com/> LinkEdin: https://ca.linkedin.com/in/tadilo-endeshaw-bogale G-Scholar: https://scholar.google.ca/citations?user=KVujBDsJ&hl=en Youtube: https://www.youtube.com/channel/UC27HXaVxXlKk88Vujkccwwg ___ Discuss-gnuradio mailing list Discuss-gnuradio@gnu.org https://lists.gnu.org/mailman/listinfo/discuss-gnuradio
[Discuss-gnuradio] Final Deadline 07 March, CROWMCOM Workshop on Cognitive Radio for 5G
Apologies if you receive multiple copies of this call. CALL FOR PAPERS === CROWNCOM Workshop on Cognitive Radio for 5G Networks April 21-23, 2015 Doha, Qata Accepted paper will be indexed by IEEExplore. http://crowncom.org/2015/show/workshop-CR5GN https://www.dropbox.com/s/68j9rz80kdsa2tn/CFP_Workshop_on_5G.pdf?dl=0 To submit papers follow the following steps 1. Login to the http://confy.eai.eu/entry.html (Create user name and password if first time user) 2. Click Go to my conferences 3. Scroll down and select "Workshop - Cognitive Radio for 5G Networks" in the icon CROWNCOM 2015 4. Click the submit paper link and provide the paper details. == Important dates - • Paper submission deadline: March 07, 2015 • Acceptance Notification: March 15, 2015 • Camera ready: March 18, 2015 == CROWNCOM 2015 Workshop Cognitive Radio for 5G Networks The exponential growth of wireless data traffic urged the international wireless industries and academia to lay out a new wireless network standard which is 5G. It is generally believed that the future 5G network may need to be engineered to meet a multitude of stringent requirements in terms of cost, energy and spectral efficiency, number of connected devices and latency. Cognitive Radio (CR) is one of the promising techniques to meet these requirements by exploiting underutilized spectrum bands especially at microwave frequencies where there is a spectrum crunch. CR has applications ranging from the traditional cellular to device-to-device (D2D) and vehicle-to-vehicle (V2V) communication systems via interweave, underlay and overlay dynamic spectrum access. In cellular systems, CR can enhance the overall efficiency of the network by allowing opportunistic and shared spectrum access. And for the D2D systems, massive short range connectivity which facilitates efficient data transfer is realized using CR. On the other hand, network assisted CR techniques can be leveraged in vehicular applications, such as driverless cars, learning the road traffic which consequently contribute in achieving the zero accident goal of the future intelligent transport systems (ITS). Furthermore, for multi-tier heterogeneous network (HetNet), CR can be utilized to opportunistically offload delay tolerant data traffic to different tiers and radio access technologies (RATs) which is one of the effective means to alleviate traffic congestion. Given the above promising potentials of CR technology, still a number of challenges arise including how to enable autonomous CR transmission without creating significant interference to the primary networks for Machine to Machine (M2M), D2D and HetNet communication systems. This workshop aims to gather researchers, academia, industry and regulators to present and discuss their research findings on the CR technology and, to highlight the opportunities, challenges and potentials of CR for realizing the future 5G network. The topics of interest include but are not limited to: • Dynamic spectrum sharing and access • Massive/multiple antenna and cooperative spectrum sensing • Energy and spectral efficient CR network • Resource allocation, power/interference control and management for CR network • Algorithm, signaling and protocol design for CR network • Carrier aggregation, traffic/data offloading and load balancing in shared spectrum access • Cognitive HetNet, D2D, M2M and V2V networks • Mobile, ad-hoc and multi-hop CR network • Self-powered and context aware CR network • Experimental, link and system level simulation, field trail and prototype results Contributions Submitted papers must present original materials which are not currently under review in any other conference or journal and have not been previously published. All submissions should be written in English with a maximum of 6 double column printed pages (minimum 10-point font) including figures and references. Papers exceeding 6 pages will not be reviewed at all. Authors should use the CROWNCOM Author's Kit template, ensuring IEEE Explore compatible PDF-format. More detailed information about the workshop and submission policy can be found at http://crowncom.org/2015/show/initial-submission. Workshop papers will be submitted for inclusion into IEEE Xplore as well as other Abstracting and Indexing (A&I) databases. --- Tadilo Endeshaw, PhD Postdoctor
[Discuss-gnuradio] Re Spectrum sensing Simulation Only
Hello Martin Thank you for the help. I try to run "specest_noisy_sinusoid_mtm.py" (Python script is also okey for me). However it does not run "it says no module specest". By the way I am using windows 8 OS. My goal is is to write a simple python or gnuradio code to perform the following task I have the following variables NFFT=1024 Nav=512 ampl=1 seed=1 Sampling_rate= 10k 1. Generate any real time signal (This could be done by using "gr.noise_source_f (gr.GR_GAUSSIAN, ampl, seed1)). 2. Insert throttle to control the sampling rate (i.e., gr.throttle(1, Sampling_rate)) 3. Compute the FFT (even without windowing) (i.e., NFFT samples at a time) Let me assume that after I compute FFT and I got an "x" vector of size NFFT 4. Compute the square magnitude of x (This could be done by using gr.complex_to_mag_squared(NFFT)) i.e., in matlab y=abs(x).^2 4. sum the first and second Nav samples i.e., av1=sum(y(1:512))/Nav and av2=sum(y(513:1024))/Nav 5. Then display "av1" and "av2" in a text box continuously. Note that in matlab (without GUI it is very easy task) And I feel that there should be some simple approach to do it in GNUradio Thank you again for your help --- Tadilo Endeshaw Postdoctoral Researcher Institut National de recherche Scientifique Centre Energie Matriaux Telecommunications Place Bonaventure, 800 de la Gauchetiere Ouest, Suite 6900 H5A 1K6 Montreal, QC Canada E-mail : tadilo.bog...@emt.inrs.ca tadilo...@yahoo.com (private) Personal home page: https://sites.google.com/site/tadilomypage/ From: discuss-gnuradio-bounces+tadilo.bogale=emt.inrs...@gnu.org [discuss-gnuradio-bounces+tadilo.bogale=emt.inrs...@gnu.org] On Behalf Of Martin Braun [martin.br...@ettus.com] Sent: July 30, 2014 10:01 AM To: discuss-gnuradio@gnu.org Subject: Re: [Discuss-gnuradio] Spectrum sensing Simulation Only On 07/30/2014 03:37 PM, Tom Rondeau wrote: > The easiest way to average is to use the single_pole_iir_filter to > smooth out the data stream. But note that you're coming out of the FFT > block as a vector. You can set the vector length of the single pole IIR, > but I'd have to review exactly what that means mathematically. It > probably smooths the entire vector as one as opposed to smoothing over > index i in each vector. You might have to play around with that. gr-specest might help you with that (pybombs install gr-specest, or https://github.com/kit-cel/gr-specest). M ___ Discuss-gnuradio mailing list Discuss-gnuradio@gnu.org https://lists.gnu.org/mailman/listinfo/discuss-gnuradio ___ Discuss-gnuradio mailing list Discuss-gnuradio@gnu.org https://lists.gnu.org/mailman/listinfo/discuss-gnuradio
[Discuss-gnuradio] Spectrum sensing Simulation Only
Hello Everyone I am a new to gnuradio. I would like to do simulation of spectrum sensing (Simple energy detector with single band only). Normally I have seen "usrp_spectrum_sense.py". However, that is written for USRP (and not easy to understand and modify it). Actually I have a difficulty in computing average and display it continuously in a graphical user interface. See also my grc and corresponding python code (The vector sinc block is not correct). Any help is appreciated. Thanks, --- Tadilo Endeshaw, PhD Postdoctoral Researcher Institut National de recherche Scientifique Centre Energie Matriaux Telecommunications Place Bonaventure, 800 de la Gauchetiere Ouest, Suite 6900 H5A 1K6 Montreal, QC Canada E-mail : tadilo.bog...@emt.inrs.ca tadilo...@yahoo.com (private) Personal home page: https://sites.google.com/site/tadilomypage/ SimpleEnergyDetector5.grc Description: SimpleEnergyDetector5.grc #!/usr/bin/env python ## # Gnuradio Python Flow Graph # Title: Top Block # Generated: Tue Jul 29 15:34:05 2014 ## from gnuradio import blocks from gnuradio import eng_notation from gnuradio import fft from gnuradio import gr from gnuradio import window from gnuradio.eng_option import eng_option from gnuradio.gr import firdes from grc_gnuradio import wxgui as grc_wxgui from optparse import OptionParser import wx class top_block(grc_wxgui.top_block_gui): def __init__(self): grc_wxgui.top_block_gui.__init__(self, title="Top Block") ## # Variables ## self.samp_rate = samp_rate = 1 ## # Blocks ## self.gr_vector_source_x_1 = gr.vector_source_c((0, 0, 0), True, 1024) self.gr_vector_source_x_0 = gr.vector_source_c((0, 0, 0), True, 1024) self.gr_vector_sink_x_0 = gr.vector_sink_f(1024) self.gr_add_xx_0 = gr.add_vcc(1024) self.fft_vxx_1 = fft.fft_vcc(1024, True, (window.blackmanharris(1024)), True, 1) self.blocks_throttle_0 = blocks.throttle(gr.sizeof_gr_complex*1024, samp_rate) self.blocks_complex_to_mag_squared_0 = blocks.complex_to_mag_squared(1024) ## # Connections ## self.connect((self.gr_vector_source_x_0, 0), (self.gr_add_xx_0, 1)) self.connect((self.gr_vector_source_x_1, 0), (self.gr_add_xx_0, 0)) self.connect((self.gr_add_xx_0, 0), (self.blocks_throttle_0, 0)) self.connect((self.blocks_complex_to_mag_squared_0, 0), (self.gr_vector_sink_x_0, 0)) self.connect((self.blocks_throttle_0, 0), (self.fft_vxx_1, 0)) self.connect((self.fft_vxx_1, 0), (self.blocks_complex_to_mag_squared_0, 0)) def get_samp_rate(self): return self.samp_rate def set_samp_rate(self, samp_rate): self.samp_rate = samp_rate self.blocks_throttle_0.set_sample_rate(self.samp_rate) if __name__ == '__main__': parser = OptionParser(option_class=eng_option, usage="%prog: [options]") (options, args) = parser.parse_args() tb = top_block() tb.Run(True) ___ Discuss-gnuradio mailing list Discuss-gnuradio@gnu.org https://lists.gnu.org/mailman/listinfo/discuss-gnuradio
