The last few years have witnessed a tremendous growth of the demand for wireless services and a significant increase of the number of mobile subscribers. A recent data traffic forecast from Cisco reported that the global mobile data traffic reached 1.2 zettabytes per year in 2016, and the global IP traffic will increase nearly threefold over the next 5 years. Based on these predictions, a 127-fold increase of the IP traffic is expected from 2005 to 2021. It is also anticipated that the mobile data traffic will reach 3.3 zettabytes per year by 2021, and that the number of mobile-connected devices will reach 3.5 per capita.
With such demands for higher data rates and for better quality of service (QoS), fifth generation (5G) standardization initiatives, whose initial phase was specified in June 2018 under the umbrella of Long Term Evolution (LTE) Release 15, have been under vibrant investigation. In particular, the International Telecommunication Union (ITU) has identified three usage scenarios (service categories) for 5G wireless networks: (i) enhanced mobile broadband (eMBB), (ii) ultra-reliable and low latency communications (uRLLC), and (iii) massive machine type communications (mMTC). The vast variety of applications for beyond 5G wireless networks has motivated the necessity of novel and more flexible physical layer (PHY) technologies, which are capable of providing higher spectral and energy efficiencies, as well as reduced transceiver implementations.
1. IEEE Signal Processing Magazine
2. Signal Processing Digital Library*
3. Inside Signal Processing Newsletter
4. SPS Resource Center
5. Career advancement & recognition
6. Discounts on conferences and publications
7. Professional networking
8. Communities for students, young professionals, and women
9. Volunteer opportunities
10. Coming soon! PDH/CEU credits
Click here to learn more.
10 years of news and resources for members of the IEEE Signal Processing Society
Joachim Thiemann (McGill University), “A Sparse Auditory Envelope Representation with Iterative Reconstruction for Audio Coding”, Advisor: Prof. Peter Kabal
In this thesis, the author investigates perceptual domain coding by using a representation designed to contain only the audible information regardless of whether reconstruction can be performed efficiently. The perceptual representation is based on a multichannel Basilar membrane model, where each channel is decomposed into envelope and carrier components. It is assumed that the information in the carrier is also present in the envelopes and discard the carrier components. The envelope components are sparsified using a transmultiplexing masking model and form a sparse auditory envelope representation (SAER). An iterative reconstruction algorithm for the SAER is evaluated using subjective and objective testing on speech and audio signals. It is found that some types of audio signals are reproduced very well using this method whereas others exhibit audible distortion. Except in specific cases where part of the carrier information is required, most of the audible information is present in the SAER and can be reconstructed using iterative methods.
© Copyright 2019 IEEE – All rights reserved. Use of this website signifies your agreement to the IEEE Terms and Conditions.
A not-for-profit organization, IEEE is the world's largest technical professional organization dedicated to advancing technology for the benefit of humanity.