The final program can be found here.
Wed Feb 6 Thur Feb 7 Fri Feb 8
  8.15am -  9.00am Registration Opens
  9:00am -  9.10am Conference Opening Announcements Announcements
  9.10am - 10.10am Keynote Talk
Prof. Xiaojing Huang
University of Technology Sydney
Keynote Talk
Dr. Zhibo Pang
ABB Corporate Research, Sweden
Keynote Talk
A/Prof. Vincent Y.F. Tan
National University of Singapore
10:10am- 10.40am Morning Tea Morning Tea Morning Tea
10.40am - 11.00am Invited Talk
A/Prof. Brian S. Krongold
University of Melbourne
Keynote Talk
Dr. David Soldani
Huawei Australia
(10.40am - 11.40am)
Invited Talk
Prof. Jinho Choi
Deakin University
11.00am - 11.20am Invited Talk
Prof. Wei Xiang
James Cook University
Invited Talk
Dr. Vera D. Miloslavskaya
University of Sydney
11.20am - 11.40am Invited Talk
A/Prof. Xiangyun (Sean) Zhou
Australian National University
Invited Talk
Dr. Shihao Yan
Macquarie University
11.40am - 12.00pm Invited Talk
Dr. Gayathri Kongara
Monash University
Invited Talk
Dr. Ni Ding
Data61
Invited Talk
Dr. Wei Ni
CSIRO
12:00pm - 1.30pm Lunch Lunch Close
  1.30pm - 3.10pm Poster Session
Poster Session
  3.10pm - 3.40pm Afternoon Tea Afternoon Tea
  3.40pm - 4.00pm Invited Talk
Dr. Sina Vafi
Charles Darwin University
Invited Talk
A/Prof. Parastoo Sadeghi
Australian National University
  4.00pm - 4.20pm Invited Talk
Dr. Kelvin Layton
University of South Australia
Invited Talk
Dr. Lei Yang
University New South Wales
  4.20pm - 4.40pm Invited Talk
Dr. Qinghua Guo
University of Wollongong
Invited Talk
Dr. Changyang She
University of Sydney
  4.40pm - 5.00pm Invited Talk
Dr. Jingge Zhu
University of Melbourne
Presentations of Invited Demos
(4.40pm - 5.20pm)
  5.00pm - 5.10pm Presentations by Shortlisted Candidates for Thesis Award
  5.20pm - 6.30pm - Break
  6.30pm - 9.30pm Banquet
(including awards)

Keynote Speakers


Tara Javidi

Vincent Y. F. Tan

Title: Minimum Rates of Approximate Sufficient Statistics

Abstract: Given a sufficient statistic for a parametric family of distributions, one can estimate the parameter without access to the data. However, the memory or code size for storing the sufficient statistic may nonetheless still be prohibitive. Indeed, for n independent samples drawn from a k-nomial distribution with d=k−1 degrees of freedom, the length of the code scales as d log n + O(1). In many applications, we may not need to reconstruct the generating distribution exactly. By adopting a Shannon-theoretic approach in which we allow a small error in estimating the generating distribution, we construct various approximate sufficient statistics and show that the code length can be reduced to (d/2) log n + O(1). We consider errors measured according to the relative entropy and variational distance criteria. For the code constructions, we leverage Rissanen's minimum description length principle, which yields a non-vanishing error measured according to the relative entropy. For the converse parts, we use Clarke and Barron's formula for the relative entropy of a parametrized distribution and the corresponding mixture distribution. However, this method only yields a weak converse for the variational distance. We develop new techniques to achieve vanishing errors and we also prove strong converses. The latter means that even if the code is allowed to have a non-vanishing error, its length must still be at least (d/2) log n.

This is joint work with Prof. Masahito Hayashi (Nagoya University) and was published in the Feb 2018 issue of the IEEE Transactions on Information Theory (https://ieeexplore.ieee.org/document/8115272/).

Bio: Vincent Y. F. Tan was born in Singapore in 1981. He is currently an Associate Professor in the Department of Electrical and Computer Engineering (ECE) and the Department of Mathematics at the National University of Singapore (NUS). He received the B.A. and M.Eng. degrees in Electrical and Information Sciences from Cambridge University in 2005. He received the Ph.D. degree in Electrical Engineering and Computer Science (EECS) from the Massachusetts Institute of Technology in 2011. His research interests include information theory, machine learning and statistical signal processing. He is currently a Distinguished Lecturer of the IEEE Information Theory Society (2018/19).
Victoria Kostina

Xiaojing Huang

Title: Towards Terabit Wireless Communications

Abstract: With the ever increasing demand for wireless connectivity, mobile data traffic continues to grow following the “omnify” principle, i.e., the data rate is observed to have an order of magnitude increase every five years, making wireless communication one of the most dramatic game-changing technologies. At this “omnify” pace, data rate for wireless transmission is expected to increase by a hundred time from current 10 Gbps within the next decade, achieving terabits per second. As the 5G mobile system emerges, ground based networks become more and more mature. However, there are still significant technological challenges to extend wireless coverage through the integration of space and terrestrial networks and to replace the last mile wired network with terabit wireless links. In this presentation, the evolution of wireless communication technologies is firstly reviewed, and the importance of millimetre wave radio frequency backbones in the integrated space and terrestrial networks is then addressed. An overview of the applications and technical challenges of the emerging terahertz wireless communications is given afterwards. Finally, some enabling techniques for improving spectral efficiency and power efficiency for millimetre wave and terahertz communications are discussed.

Bio: Xiaojing Huang received the B.Eng., M.Eng., and Ph.D. degrees in electronic engineering from Shanghai Jiao Tong University, Shanghai, China, in 1983, 1986, and 1989, respectively. He is currently a professor of information and communications technology with the School of Electrical and Data Engineering and the program leader of Mobile Sensing and Communications with the Global Big Data Technologies Centre, University of Technology Sydney (UTS), Sydney, Australia.

He was with the Motorola Australian Research Centre as a Senior and then Principal Research Engineer from 1998 to 2003. He had been an Associate Professor with the University of Wollongong, Wollongong, Australia, from 2004 to 2008. He had been a Principal Research Scientist with the Commonwealth Scientific and Industrial Research Organisation (CSIRO), Sydney, Australia, and the project leader of CSIRO’s microwave and millimetre wave backhaul projects from 2009 to 2014. He was a recipient of the CSIRO Chairman’s Medal and the Australian Engineering Innovation Award in 2012 for exceptional research achievements in multigigabit wireless communications. With 30 years of combined industrial, academic, and scientific research experience, he has authored over 300 book chapters, refereed journal and conference papers, major commercial research reports, and has filed 31 patents.

Professor Huang served as Technical Program Committee Chairs and/or Co-Chairs for a number of international conferences such as ISCIT (2007, 2010, 2012-2014, and 2016), ICUWB2013, WPMC2014, and VTC2017-Spring.
Zhibo Pang

Zhibo Pang

Title: Last Mile Connectivity: the Bottleneck of Mission Critical Industrial IoT

Abstract: As important fuel of the fourth revolution of industries (Industry 4.0), Industrial IoT especially the industrial wireless connectivity has become the new driver of research in communications. To deliver the big values promised by the Industrial IoT, closing the control and optimization loops is the first step. Despite continuous efforts in the recent decades by telecom and industries, last mile connectivity is still the bottleneck for closed loop control and optimization in mission critical applications. There are significant differences between the two different worlds, consumer connectivity vs. industrial connectivity. Noticeable mistakes have been made when previous industrial connectivity technologies were developed such as the WireelssHART. To fully address the requirements of critical Industrial IoT applications (such as mining automation, autonomous robotics, power systems, factory of future, etc.), much higher performances are required including multi-gigabit-per-second data rate, sub-microsecond latency, and ultra-high reliability. Basic feasibility has been proven by the latest work on Wireless HP (high performance) at ABB based on FPGA-based SDR (software defined radio) which has outperformed the 5G URLLC by x 10 times in terms of latency. As highlighted in future research agenda, new fundamental design, standards, and chips are demanded.

Bio: Dr. Zhibo Pang, PhD&MBA received B.Eng. in Electronic Engineering from Zhejiang University, Hangzhou, China in 2002, MBA in Innovation and Growth from University of Turku, Turku, Finland in 2012, and PhD in Electronic and Computer Systems from the Royal Institute of Technology (KTH), Stockholm, Sweden in 2013. He is currently a Principal Scientist on Wireless Communications at ABB Corporate Research, Västerås, Sweden, leading projects in digitalization solutions for smart buildings and homes, robotics and factories, healthcare and logistics, power electronics and power systems. He is also Affiliated Faculty and PhD Supervisor at Royal Institute of Technology (KTH). Before joined ABB, he was co-founder and CTO of startups such as Ambigua Medito AB. He is a Senior Member of IEEE and Co-Chair of the Technical Committee on Industrial Informatics. He is Associate Editor of IEEE Transactions on Industrial Informatics and IEEE Journal of Biomedical and Health Informatics, Guest Editor of Proceedings of the IEEE, IEEE Internet of Things Journal, and IEEE Reviews in Biomedical Engineering, etc. He was awarded the “2016 Inventor of the Year Award” by ABB Corporate Research Sweden. He has 60+ patents and 50+ refereed journal papers and 40+ conference papers in these areas.
David Soldani

David Soldani

Title: 5G Developments and AI-Enabled Automation

Abstract: 5G systems and AI platforms have been attracting a lot of attention in recent years and plenty of results for horizontal and vertical sectors have been attained globally. The talk provides a snapshot of the global status of national 5G spectrum plans and reviews the main progresses in 3GPP standards. The main challenges of 5G deployments and solutions thereof are discussed next. Within this framework, AI applications to energy saving, network performance and quality of experience improvement are also presented. Conclusions are drawn on new business, research and innovation directions.

Bio: David Soldani received a M.Sc. degree, Laura Vecchio Ordinamento, in Electronic Engineering with magna cum laude from Università degli Studi di Firenze, Italy, in 1994; and a D.Sc. degree in Technology with distinction from Helsinki University of Technology (Aalto University), Finland, in 2006. In 2014 and 2016, he was appointed Visiting Professor and Industry Professor at University of Surrey, UK, and University of Technology Sydney, Australia, respectively.

Dr. Soldani has been active in the ICT industry for more than 20 years, successfully working on 500+ research, innovation and customer services projects for 2G, 3G, 4G and 5G ICT systems and services, and contributing to 1000+ quality deliverables – from strategic research and innovation strategies, business and work plans formulation, to modelling, simulations, emulations and proof of concepts of innovative solutions, products and services with partners and customers, globally.

He is currently back at Huawei Technologies, serving as Chief Technology Officer (CTO) in Australia. Areas of his responsibilities and expertise include, but not limited to: future wireless, network, big data value, artificial intelligence, IoT and multimedia technologies.

Prior to that he was at Nokia, as Head of 5G Technology, e2e, global, and in various technical and research management positions. Before re-joining Nokia in 2016, he was for eight years at Huawei European Research Centre, Germany, serving as Head of IP Transformation Research Centre (IPTRC), Head of Network Solution R&D and, subsequently, Head of Central Research Institute (CRI) and VP Strategic Research and Innovation, in Europe; and represented Huawei in the Board of Directors of The 5G Infrastructure Association (5G-IA) and NetWorld2020 European Technology Platform (ETP), in Europe.

He has been selected many times to receive special awards in recognition of his role, commitment, professionalism, and outstanding contribution in the ICT industry; and in 2016, he was granted a Distinguished Talent (DT) visa for his profession by the Australian Government. He has published or presented numerous international papers, contributed to the publication of many books, and holds several international patents.

Invited Talk


Title: An Australia’s First – JCU’s Internet of Things Engineering Program

Abstract: It is well known that the Internet of Things (IoT) technology is one of the most crucial digital infrastructure for the fourth industrial revolution that is revolutionizing the human society. Some consider IoT technology the frontend of big data. We would argue that IoT is a data-driven technology, which is composed of three layers, i.e., the data collection layer, data communications layer, and data processing layer. This three-layer stratification well explains why IoT technology serves as a foundation to and is inseparable from machine learning (ML) / artificial Intelligence (AI). James Cook University (JCU) prides itself on providing Australia’s first IoT Engineering degree program that is accredited by Engineers Australia. Huawei also set up its first official laboratory with JCU, the JCU-Huawei Narrowband IoT Laboratory opened in February 2017. This talk will walk you through the first IoT course created in Australia, as well as the IoT projects and industry engagement that have been achieved at JCU.

Bio: Wei Xiang is currently the Founding Professor and Inaugural Head of Discipline of Internet of Things Engineering at James Cook University, Cairns, Australia. He is a TEDx Speaker, and an elected Fellow of the IET and Engineers Australia. He received the 2016 TNQ Innovation Award, 2017 Engineers Australia Cairns Engineer of the Year, and 2018 Pearcey Foundation Hall of Fame. He was a co-recipient of four Best Paper Awards at 2019 WiSATS, 2015 WCSP, 2011 IEEE WCNC, and 2009 ICWMC. He has been awarded several prestigious fellowship titles, including a Queensland International Fellow (2010-2011) by the Queensland Government, an Endeavour Research Fellow (2012-2013) by the Australian Government, a Smart Futures Fellow (2012-2015) by the Queensland Government, and a JSPS Invitational Fellow jointly by the Australian Academy of Science and Japanese Society for Promotion of Science (2014-2015). He is the Vice Chair of the IEEE Northern Australia Section. He was an Editor for IEEE Communications Letters (2015-2017), and is an Associate Editor for Springer’s Telecommunications Systems. He has published over 220 peer-reviewed papers, of which nearly 100 are IEEE journal articles. He has served in a large number of international conferences in the capacity of General Co-Chair, TPC Co-Chair, Symposium Chair, etc. His research interest falls under the broad areas of communications and signal processing, particularly the Internet of Things, and coding and signal processing for multimedia communications systems.
Title: proving Computational Efficiency of Communication for Omniscience and Successive Omniscience

Abstract: For a group of users in V where everyone observes a component of a discrete multiple random source, the process that users exchange data so as to reach omniscience, the state where everyone recovers the entire source, is called communication for omniscience (CO). We first consider how to improve the existing complexity O(|V|^2 * SFM(|V|) of minimizing the sum of communication rates in CO, where SFM(|V|) denotes the complexity of minimizing a submodular function. We reveal some structured property in an existing coordinate saturation algorithm: the resulting rate vector and the corresponding partition of V are segmented in $\alpha$, the estimation of the minimum sum-rate. A parametric (PAR) algorithm is then proposed where, instead of a particular $\alpha$, we search the critical points that fully determine the segmented variables for all $\alpha$ so that they converge to the solution to the minimum sum-rate problem and the overall complexity reduces to O(|V| * SFM(|V|)).

For the successive omniscience (SO), we consider how to attain local omniscience in some complimentary user subset so that the overall sum-rate for the global omniscience still remains minimum. While the existing algorithm only determines a complimentary user subset in O(|V| * SFM(|V|)) time, we show that, if a lower bound on the minimum sum-rate is applied to the segmented variables in the PAR algorithm, not only a complimentary subset, but also an optimal rate vector for attaining the local omniscience in it are returned in O(|V| * SFM(|V|)) time. Finally, we show how the proposed PAR algorithm is applied to the hierarchical clustering task based on the multivariate mutual information measure.

Bio: Ni Ding received the B.C.A. degree from the Shanghai Second Polytechnic University, China, in 2005, the B.E. degree in Telecommunications (1st class honors) from the University of New South Wales, Australia, in 2012 and PhD degree in Electrical Engineering from the Australian National University (ANU) in 2017. From September 1998 to August 2006, She was an associate engineer in Shanghai Telecom, China. In 2016, the last year of her PhD study at ANU, she was employed by the Institute of Network Coding, The Chinese University of Hong Kong, as a junior research assistant for three months. She is now a postdoctoral fellow at Data61.

Her research interests generally include optimizations in information theory, wireless communications, signal processing and machine learning. She is currently interested in the discrete and combinatorial optimization problems raised in the following areas: information theoretic privacy-preserving techniques , lossless and lossy data compression, optimal information flow over a graph/hypergraph, discrete event control in cross-layer adaptive modulation and game theory (in particular, the games with strong structures, e.g., supermodular and convex games).
Title: A submodularity-based agglomerative clustering algorithm for the privacy funnel

Abstract: We propose an efficient iterative agglomerative clustering (IAC) algorithm for the privacy funnel (PF) based on the minimization of the difference of submodular functions (IAC-MDSF). The aim of PF is to maintain an acceptable mutual information between the useful data $X$ and released data $\hat X$ while minimizing the privacy leakage, which is measured as the mutual information between released data $\hat X$ and sensitive data $S$. Our IAC-MDSF algorithm starts with the original alphabet for $X$ and iteratively merges the elements in the current alphabet that minimizes the Lagrangian function $I(S; \hat X) - \lambda I(X; \hat X)$. We prove that the best merge in each iteration of IAC-MDSF can be searched efficiently over all subsets of $\hat X$ by existing MDSF algorithms. We show that the IAC-MDSF algorithm also applies to the information bottleneck (IB), a dual problem to PF. Using a real dataset, we show that our IAC-MDSF algorithm outperforms the existing iterative pairwise merge approaches for both PF and IB and is computationally much less complex.We propose an efficient iterative agglomerative clustering (IAC) algorithm for the privacy funnel (PF) based on the minimization of the difference of submodular functions (IAC-MDSF). The aim of PF is to maintain an acceptable mutual information between the useful data $X$ and released data $\hat X$ while minimizing the privacy leakage, which is measured as the mutual information between released data $\hat X$ and sensitive data $S$. Our IAC-MDSF algorithm starts with the original alphabet for $X$ and iteratively merges the elements in the current alphabet that minimizes the Lagrangian function $I(S; \hat X) - \lambda I(X; \hat X)$. We prove that the best merge in each iteration of IAC-MDSF can be searched efficiently over all subsets of $\hat X$ by existing MDSF algorithms. We show that the IAC-MDSF algorithm also applies to the information bottleneck (IB), a dual problem to PF. Using a real dataset, we show that our IAC-MDSF algorithm outperforms the existing iterative pairwise merge approaches for both PF and IB and is computationally much less complex.

Bio: Parastoo Sadeghi is an Associate Professor at the Research School of Engineering, the Australian National University, Canberra, Australia. She received the BSc and MSc degrees in electrical engineering from Sharif University of Technology, Tehran, Iran, in 1995 and 1997, respectively, and the PhD degree in electrical engineering from the University of New South Wales, Sydney, Australia, in 2006. She is currently serving as an Associate Editor of Coding Techniques for the IEEE Transactions of Information Theory. Her research interests are mainly in the areas of network coding, information theory, wireless communications theory, and signal processing.
Title: Compute-Forward Multiple Access (CFMA)

Abstract: We discuss Compute-Forward Multiple Access (CFMA), a novel multiple access technique which is provably capacity achieving, and at the same time enjoys low-complexity practical implementations. This attractive feature makes CFMA a promising candidate for NOMA (Non-Orthogonal Multiple Access) techniques. Bio: Jingge Zhu received the PhD degree from the Ecole Polytechnique Federale Lausanne (EPFL), Switzerland, in 2016. From 2016 to 2018, he was a postdoctoral researcher at the University of California, Berkeley, USA. He is currently a Lecturer in the Department of Electrical and Electronic Engineering at the University of Melbourne. His research interests include information theory with applications to communication, computation, and control systems.

Bio: Jingge Zhu received the PhD degree from the Ecole Polytechnique Federale Lausanne (EPFL), Switzerland, in 2016. From 2016 to 2018, he was a postdoctoral researcher at the University of California, Berkeley, USA. He is currently a Lecturer in the Department of Electrical and Electronic Engineering at the University of Melbourne. His research interests include information theory with applications to communication, computation, and control systems.
Title: Design of Error-Correction Codes Decodable as Polar Codes

Abstract: In this talk I will give an introduction to polar codes and describe a class of linear block error-correction codes which may be efficiently decoded in the same way as polar codes. First, we look at structure of classical polar codes and discuss its relation to other well-known codes, e.g. Reed-Muller codes, Bose-Chaudhuri-Hocquenghem codes and generalized concatenated codes. Second, we consider methods for soft-decision decoding of polar codes and discuss correction capability of polar codes. Third, we identify variations of polar codes demonstrating higher correction capability compared to classical polar codes.

Bio: Vera Miloslavskaya received B.Sc., M.Sc. and PhD degrees from the Peter the Great St. Petersburg Polytechnic University (SPbPU) in 2010, 2012 and 2015, respectively. During her years in SPbPU, she participated in research projects for Huawei, Samsung and EMC. These projects were related to wireless communication and storage systems. 2016-2018 she has been with Cloud Crowding Corp. Datomia, as a Research Scientist. She is currently a Postdoctoral Researcher in Telecommunications in the School of Electrical and Information Engineering at the University of Sydney. Her research interests are coding theory, information theory, distributed storage systems and wireless communications.
Title: Physical Layer Security: Perfect Secrecy, Partial Secrecy, Covertness

Abstract: This talk will provide a brief discussion on performance metrics used in physical layer security. In particular, most existing studies make use of metrics defined based on perfect secrecy conditions, which will be discussed first. We will then look at some recently developed secrecy metrics based on partial secrecy and discuss its advantages. Towards the end of the talk, we will move beyond secrecy of content and discuss covertness of communication which is an increasingly hot topic in physical layer security.

Bio: Xiangyun (Sean) received the Ph.D. degree from the Australian National University in 2010. Currently, he works as an Associate Professor at the Australian National University. His research interests are in the areas of communication theory and wireless networks with recent focus on physical layer security, backscatter communications, energy harvesting and wireless powered communications, machine-to-machine communications. http://users.cecs.anu.edu.au/~xyzhou/Default.html
Title: Gaussian Signalling for Covert Communications

Abstract: In covert communications, a transmitter desires to transmit information to a legitimate receiver without being detected by a warden. In this talk, we examine the optimality of Gaussian signalling for covert communications. Considering additive white Gaussian noise at both the receiver and the warden, we prove that Gaussian signalling is optimal in terms of maximizing the mutual information between transmitted and received signals subject to one covertness constraint based on KL divergence. More interestingly, we also prove that Gaussian signalling is not optimal for covert communications subject to another covertness constraint, for which as we explicitly show a skew-normal signalling can outperform Gaussian signalling in terms of achieving higher mutual information subject to the same covertness constraint. We also clarify some challenges and future research directions in the context of covert communications.

Bio: Shihao Yan received the Ph.D degree in Electrical Engineering from The University of New South Wales, Sydney, Australia, in 2015. He received the B.S. in Communication Engineering and the M.S. in Communication and Information Systems from Shandong University, Jinan, China, in 2009 and 2012, respectively. From 2015 to 2017, he was a Postdoctoral Research Fellow in the Research School of Engineering, The Australian National University, Canberra, Australia. He is currently a Research Fellow in the School of Engineering, Macquarie University, Sydney, Australia. He has published about 30 journal articles, out of which 10 are first-authored IEEE Transactions and 1 is a highly cited article. His current research interests are in the areas of wireless communications and statistical signal processing, including physical layer security, covert communications, and location spoofing detection.
Title: Ultra-reliable Low-latency Communications: scenarios, solutions, and open issues

Abstract: Ultra-reliable low-latency communications (URLLC) has been considered as one of the three new application scenarios in the 5th Generation (5G) New Radio (NR), where the physical layer design aspects have been specified. With the 5G NR, we can guarantee the reliability and latency in radio access networks. However, for scenarios where the transmission involves both radio access and wide area core networks, the delay in radio access networks only contributes to part of the end-to-end (E2E) delay. In this talk, we outline the delay components and packet loss probabilities in three typical communication scenarios of URLLC, i.e., local area networks, mobile edge computing networks, and wide-area large-scale networks. Then, we summarize possible solutions in these three scenarios respectively. Finally, we discuss the open issues in URLLC.

Bio: Changyang She (S’12-M’17) received his B. Eng degree in Honors College (formerly School of Advanced Engineering) of Beihang University (BUAA), Beijing, China in 2012 and Ph.D. degree in School of Electronics and Information Engineering of BUAA in 2017. From 2017 to 2018, he was a postdoctoral research fellow in Singapore University of Technology and Design. Since 2018, he has become a postdoctoral research associate in the University of Sydney. His research interests lie in the areas of ultra-reliable and low-latency communications, tactile internet, big data/machine learning for resource allocation in wireless networks and energy efficient transmission in 5G communication systems.
Title: Machine-Type Communication for the IoT

Abstract: The Internet of Things (IoT) is the network to provide the connectivity for physical devices including sensors, which will have a huge impact on future industry as well as our daily life, In cellular systems (e.g., 5G), machine-type communication (MTC) is considered for the IoT with random access. For example, in the long term evolution-advanced (LTE-A) system, random access channel (RACH) procedure and narrowband IoT (NB-IoT) have been proposed for MTC to support massive connectivity. In this talk, we discuss MTC and a new random access scheme, called compressive random access (CRA) with its key features. We also show that CRA is an attractive scheme not only for random access, but also for physical-layer authentication as lightweight security in cellular IoT.

Bio: Jinho Choi was born in Seoul, Korea. He received B.E. (magna cum laude) degree in electronics engineering in 1989 from Sogang University, Seoul, and M.S.E. and Ph.D. degrees in electrical engineering from Korea Advanced Institute of Science and Technology (KAIST) in 1991 and 1994, respectively. He is with the School of In- formation Technology, Deakin University, Burwood, VIC 3125, Australia, as a Professor. Prior to joining Deakin in 2018, he was with Swansea University, United Kingdom, as a Professor/Chair in Wireless, and Gwangju Institute of Science and Technology (GIST), Korea, as a Professor. His research interests include the Internet of Things (IoT), wireless communications, and statistical signal processing. He authored two books published by Cambridge University Press in 2006 and 2010. Prof. Choi received the 1999 Best Paper Award for Signal Processing from EURASIP, 2009 Best Paper Award from WPMC (Conference), and is Senior Member of IEEE. Currently, he is an Editor of IEEE Trans. Communications and IEEE Wireless Communications Letters and had served as an Associate Editor or Editor of other journals including IEEE Communications Letters, Journal of Communications and Networks (JCN), IEEE Trans. Vehicular Technology, and ETRI journal.
Title: Compensation for channels with data-dependent distortions

Abstract: Communication channels that can be modelled with data-dependent noise on the received symbols are considered. This includes satellite and optical channels with various types of distortion. A new demapper is proposed to incorporate the covariance of the received symbol clusters to capture the varying noise statistics across the constellation. Two communication scenarios are considered, demonstrating the demapper is advantageous when a system is dominated by distortion as opposed to thermal noise. Channel coding considerations are presented, and reductions up to 4 dB in the required SNR are achieved.

Bio: Kelvin Layton is a research fellow at the Institute for Telecommunications Research at the University of South Australia. He completed his B. Eng and B. Info Tech degrees at Queensland University of Technology in 2005. He worked as a software engineer from 2006-2008 and then completed his PhD degree from the University of Melbourne in 2013. He developed new technologies in magnetic resonance imaging (MRI) before switching to telecommunications research. His current research interests are in signal processing and estimation algorithms with applications to satellite communications, beamforming and high-speed downlinks.
Title: An efficient bound for burst error correcting capability of binary cyclic cyclic codes

Abstract: Burst error has a high impact on the quality of telecommunication and storage systems since it affects more than one sequence of symbols. The effect of this error can be mitigated by a reliable Forward Error Correcting (FEC) code. Depending on the code’s characteristics, errors are corrected only if the allocated length of code is greater than the length of error patterns. In this case, an optimum code can be formed when its burst error correcting capability meets a particular bound, named as Reiger bound.

Binary cyclic codes are amongst the most important types of burst error correcting codes. There are several methods that verify their performance, which are mainly constructed based on the cyclic property. As one of the newest methods, the burst error correcting capability of a cyclic code can be determined based on its parity check circulant matrix. It is constructed by specifying the length and position of the unique maximal zero spans from module-2 sums of the matrix columns. Its complexity is proportional to the number of columns involved in the calculations. Hence, a large number of sums are evident for codes with a large number of parity bits, whose correcting capabilities are close or equal to the Reiger bound value.

In order to simplify complexity of the above technique, algorithms for estimating burst error correcting capability of cyclic codes are demonstrated. These are formed based on structure of the parity check polynomial and properties of the circulant matrix. Then, a method for constructing cyclic codes with the optimum (or high) performance in correction of the burst error is presented.

Bio: Sina Vafi received the PhD degree from The University of Wollongong (UoW) in 2006. After completion of his PhD, at UoW, he was involved in a project relevant to design and implementation of broadband wireless mesh networks. In 2007, he joined Charles Darwin University (CDU) as a lecture and is currently a Senior Lecturer of Electrical and Electronics Engineering. At CDU, he also leads research projects on algebraic coding theory and its applications for wireless video transmission systems. He has been a TPC member of international conferences as well as reviewers for number of IEEE and IET journals.

He has also five year’s industry experience in research, design and implementation of optical and broadband wireless networks.
Title: Partially Information-Coupled Codes

Abstract: Spatially coupled codes, such as SC-LDPC codes and SC Turbo-like codes, have shown considerable coding gain over their uncoupled counterparts. However, these codes are generally tightly coupled in the sense that several coupled code blocks have to be decoded jointly to achieve a reasonable BER performance. This leads to an increased decoder implementation complexity compared to the uncoupled counterparts. We propose the concept of partially information coupling in which a code block shares a part of its information bits with its neighboring code blocks. This coupling concept can explore the coupling gain while keep the underlying decoder for each code block unchanged. We apply this concept to construct partially information-coupled Turbo codes, LDPC codes and Polar codes. Simulation results demonstrated that these codes can achieve considerable coding gains compared to their uncoupled counterparts.

Bio: Lei Yang received his B.E. and M.Sc. degrees in electronics engineering from Beihang University, Beijing, China, in 2004 and 2007, respectively, and his Ph.D. degree in communications and information system from Beijing Institute of Technology, Beijing, China, in 2015. He is awarded DECRA in 2018. He is currently a Research Fellow at The University of New South Wales, Sydney, Australia. His current research interests include ultra-high-speed ultra-reliable commutations, spectrum-efficient coded modulation, physical layer network coding and iterative signal processing.
Title: Decentralize Fog Computing for Future Mobile Edge Cloud

Abstract: Fog computing is a promising technique which brings computing and storage capability of networks to the point of data capture, and hence provides fast response and alleviates congestions at network backbones. The effective design and operation of fog computing remain unaddressed, given the sheer size of an edge cloud and potentially selfish behaviours of edge devices. This talk presents a few recent breakthroughs in which we are able to decentralize the operations of fog computing with asymptotically diminishing optimality loss. We are also able to incentivise selfish edge servers to participate in fog computing, and discourage their selfish behaviours by designing distributed tit-for-tat mechanisms.

Bio: Dr Wei Ni was awarded BE and PhD degrees in Electronics Engineering in 2000 and 2005, respectively, both from Fudan University, Shanghai, China. He is a Team Leader at the CSIRO, and an adjunct professor at the University of Technology Sydney (UTS), since 2009. Prior to this, he was a Senior Researcher at Nokia Devices R&D (Jan 2008 – March 2009), and a Deputy Project Manager at Alcatel-Lucent Bell Labs Research & Innovation Centre (Jan 2005 – Dec 2007). His research interest covers stochastic optimization, game theory and graph theory, as well as their applications to integrity, security and efficiency of Cyber Physical System.

Dr Ni has published over 150 journal and conference papers. He has also contributed significantly to the industry with successful proposals and launches of an Alcatel-Lucent internal venture and two projects, 25 patents and 10 accepted standard proposals. His scientific breakthroughs include the world's fastest wireless broadband demonstrator; patented adaptive topology of software-defined radio network; and quality-of-service provision to unreliable energy-harvesting powered wireless links.

Dr Ni serves as Vice Chair of IEEE VTS NSW chapter and Editor of IEEE Trans. Wireless Communications since 2018, served as Secretary of IEEE VTS NSW chapter (2015 – 2018), Editorial Board Member for Hindawi Journal of Engineering (2012 – 2015), Track Chair of VTC2017-spring, Track Co-chair of VTC2016-spring, Publication Chair of BodyNet 2015, Student Travel Grant Chair of WPMC 2014, TPC member of ICC’16-CoCoNet, ICCC’15, ICC’14, CHINACOM 2014, EICE2014, and IEEE WCNC 2010. He is a Senior Member of IEEE.
Title: Message Passing Based Bayesian Receiver for Grant Free NOMA

Abstract: Grant free non-orthogonal multiple access (NOMA) is promising to support massive connectivity for internet-of-things and machine-type communications in future wireless networks. In grant free NOMA, user activity detection is performed at receiver to identify active users, so that transmission latency and control signalling overhead can be significantly reduced. We study Bayesian receivers to achieve joint user activity detection and channel estimation / joint user activity and multiuser detection in grant free NOMA, and their efficient implementations with message passing techniques.

Bio: Dr Qinghua Guo received his PhD degree in electronic engineering from City University of Hong Kong in 2008. He is now an Associate Professor with the School of Electrical, Computer and Telecommunications Engineering, University of Wollongong, and an Adjunct Associate Professor with the School of Engineering, University of Western Australia. Dr Guo was a recipient of the inaugural ARC DECRA in 2012. His research interest includes telecommunications, communication signal processing, optoelectronic signal processing, etc.
Title: Role of Software Defined radio in 5G-like studies at Monash University

Abstract: In this presentation, I will be sharing my experience on the role of Software Defined radio (SDR) in the evaluation of waveforms for 5G systems. Specifically, my presentation will focus on massive machine type communications (mMTC) operating in asynchronous transmission environments. Standard CP-OFDM and various versions of filtered-OFDM waveforms are currently under consideration for extreme mobile broadband (eMBB) application of 5G systems. However, our study on SDR platform reveal that these waveform solutions are not well suited for mMTC scenarios. A comparison of time and frequency characteristics of the three potential candidate waveforms on the SDR platform will be presented. Over the air performance of the three waveforms in asynchronous environments will be further discussed.

Bio: Dr Gayathri Kongara is a lecturer at Monash University in the Faculty of Engineering with technical experience in the areas of Telecommunications and Signal processing. At Monash, she established a new capability in the Electrical and computer systems engineering (ECSE) department to teach advanced radio system design concepts using hands-on experimentation on the software defined radio (SDR) platform. She is currently working on the design and prototyping of 5G Physical layer (PHY) at Monash. Prior to joining Monash, she held a research-engineering role at the Wireless Research Center (WRC) at University of Canterbury, NZ.
Title: Coordinated Multipoint OFDM Transmission for Maximising Capacity or Energy Harvesting

Abstract: We highlight a few of our works in the area of coordinated multipoint OFDM transmission for both maximising capacity or harvested energy in a multiple-input, single-output (MISO) system. Optimisation problems are formulated based on distributed antennas having knowledge of channel state information (CSI) for all subchannels. When the CSI is magnitude plus phase, we utilise co-phasing at the coordinated transmission points to formulate and solve convex optimisation problems. The results are some interesting theorems that, at first glance, may even seem counterintuitive to classical waterfilling theory. Simulation results are given to demonstrate these theorems and look deeper into the intuition behind them. Finally, we briefly outline our work on non-coherent (magnitude-only CSI) coordinated transmission for capacity maximisation and energy harvesting in MISO systems.

Bio: Brian Krongold received the B.S., M.S. and Ph.D. degrees in electrical engineering in 1995, 1997, and 2001, respectively, from the University of Illinois at Urbana-Champaign (UIUC). He was as a Research Assistant at the Coordinated Science Laboratory at UIUC from 1995 to 2001. From December 2001 to December 2004, he was a Research Fellow in the ARC Special Research Centre for Ultra-Broadband Information Networks in the Department of Electrical and Electronic Engineering, University of Melbourne, Parkville, Australia. He then received an ARC Postdoctoral Research Fellowship and held this from 2005 to 2007. In the first half of 2011, Brian was on sabbatical at Alcatel-Lucent (now Nokia) Bell Labs in Murray Hill, New Jersey, USA. He is currently an Associate Professor at the University of Melbourne. His research interests include both wireless and optimal communication systems.Brian Krongold received the B.S., M.S. and Ph.D. degrees in electrical engineering in 1995, 1997, and 2001, respectively, from the University of Illinois at Urbana-Champaign (UIUC). He was as a Research Assistant at the Coordinated Science Laboratory at UIUC from 1995 to 2001. From December 2001 to December 2004, he was a Research Fellow in the ARC Special Research Centre for Ultra-Broadband Information Networks in the Department of Electrical and Electronic Engineering, University of Melbourne, Parkville, Australia. He then received an ARC Postdoctoral Research Fellowship and held this from 2005 to 2007. In the first half of 2011, Brian was on sabbatical at Alcatel-Lucent (now Nokia) Bell Labs in Murray Hill, New Jersey, USA. He is currently an Associate Professor at the University of Melbourne. His research interests include both wireless and optimal communication systems.

Poster Session – 6 Feb 2019 (1.30pm-3.10pm)


Authors:
Title:
Institution:
Khurram Shahzad, Xiangyun Zhou, Shihao Yan, Jinsong Hu, Feng Shu and Jun Li
Achieving Covert Wireless Communications Using a Full-Duplex Receiver
ANU
Authors:
Title:

Institution:
Bijaya Paudel, Dr. Sina Vafi
An Unequal Error Protection of Quasi-Cyclic Low Density Parity Check (QC-LDPC) Codes Based on Combinatorial Designs
Charles Darwin University
Authors:
Title:
Institution:
Jin Yeong Tan, Lawrence Ong, Behzad Asadi
A Simplified Coding Scheme for the Memoryless Broadcast Channel with Individual Secrecy
University of Newcastle
Authors:
Title:

Institution:
Zhanwei Hou, Changyang She, Yonghui Li, Tony Quek, Branka Vucetic
Burstiness Aware Bandwidth Reservation for Ultra-reliable and Low-latency Communications (URLLC) in Tactile Internet
USYD
Authors:
Title:
Institution:
Simin Xu, Biao He, Nan Yang, and Hamid Jafarkhani
Coverage Analysis of Millimeter Wave Cellular Networks with Spatial Correlation
ANU
Authors:
Title:
Institution:
Changyang She, Yonghui Li, Branka Vucetic
Cross-layer Design for Ultra-Reliable Low-Latency Communications
USYD
Authors:
Title:
Institution:
Prameesha S. Weerasinghe, Sarah M. Erfani, Tansu Alpcan, Christopher Leckie, Margreta Kuijper
Detection of Anomalous Communications with SDRs and Unsupervised Adversarial Learning
University of Melbourne
Authors:

Title:

Institution:
Trang Ngoc Cao, Arman Ahmadzadeh, Vahid Jamali, Wayan Wicke, Phee Lep Yeoh, Jamie Evans, and Robert Schober
Diffusive Mobile Molecular Communication for Controlled-Release Drug Delivery with an Absorbing Receiver
University of Melbourne
Authors:
Title:

Institution:
Min Qiu, Yu-Chih Huang and Jinhong Yuan
Downlink Non-Orthogonal Multiple Access without SIC for Block Fading Channels: An Algebraic Rotation Approach
UNSW
Authors:
Title:
Institution:
Mohsen Mohammadkhani Razlighi, Nikola Zlatanov, and Petar Popovski
Dynamic Time-Frequency Division Duplex
Monash University
Authors:
Title:
Institution:
Zainab Zaidi, Hazer Inaltekin, Jamie Evans
Energy Consumption Study of small cells, CRAN, split signalling and data dense deployments
University of Melbourne
Authors:
Title:
Institution:
Azam Mehboob, Kelvin Layton, William Cowley and Gottfried Lechner
Improved Modulation and Coding for Spectral Efficient Communications
University of South Australia
Authors:
Title:
Institution:
Shalanika Dayarathna
Instantaneous Sum Rate Throughput Optimization in General Communicaion Networks
University of Melbourne
Authors:
Title:
Institution:
Zhuo Sun, Zhiqiang Wei, Lei Yang, Jinhong Yuan, Xingqing Cheng, and Lei Wan
Joint User Identification and Channel Estimation in Massive Connectivity with Transmission Control
UNSW
Authors:
Title:
Institution:
Muhammad Usman Riaz, Hamdan Awan, Chun Tung Chou
Maximum a-posteriori demodulation for molecular communication with spatially partitioned receivers
UNSW
Authors:
Title:
Institution:
Yuting Fang, Adam Noel, Andrew W. Eckford, and Nan Yang
On the Analysis of Bacterial Cooperation with a Characterization of 2D Signal Propagation
ANU
Authors:
Title:
Institution:
Muhammad Abu Hanif and Sina Vafi
Construction of efficient product polar codes based on two half-rate polar codes
Charles Drawing University

Poster Session – 7 Feb 2019 (1.30pm-3.10pm)


Authors:
Title:
Institution:
Armin Bazrafkan and Nikola Zlatanov
On the Capacity of Massive MIMO With One-Bit ADCs and DACs at the Receiver and the Transmitter
Monash University
Authors:
Title:
Institution:
Zhiqiang Wei, Lei Yang, Derrick Wing Kwan Ng, and Jinhong Yuan
On the Performance Gain of NOMA over OMA in Uplink Single-cell Systems
UNSW
Authors:
Title:
Institution:
Sheeraz A. Alvi, Xiangyun Zhou, and Salman Durrani.
Optimal Compression and Transmission Rate Control for Node-Lifetime Maximization
ANU
Authors:
Title:
Institution:
Chunhui Li, Nan Yang, and Shihao Yan
Optimal Transmission of Short-Packet Communications in Multiple-Input Single-Output Systems
ANU
Authors:
Title:

Institution:
Yuyue Luo, J. Andrew Zhang
Optimization and Quantization of Multibeam Beamforming Vector for Joint Communication and Radio Sensing
UTS
Authors:
Title:
Institution:
Michael Fasulakis
Peak-to-Average-Power Reduction and MIMO Applicability of PCC OFDM to 5th Generation Networks
Monash University
Authors:
Title:
Institution:
Xiaolun Jia and Xiangyun Zhou
Performance Characterisation of Ambient Backscatter Relaying Systems
ANU
Authors:
Title:
Institution:
Samiru Gayan, Hazer Inaltekin, Rajitha Senanayake and Jamie Evans
Phase Modulated Communication with Low-Resolution ADCs
University of Melbourne
Authors:
Title:
Institution:
Chentao Yue, Mahyar Shirvanimoghadda, Yonghui Li, Branka Vucetic
Segmentation-Discarding Ordered-Statistic Decoding for Linear Block Codes
USYD
Authors:
Title:
Institution:
Zohair Abu-Shaban, Henk Wymeersch, Thushara Abhayapala, Gonzalo Seco-Granados
Single-Anchor Two-Way Localization Bounds for 5G mmWave Systems: Two Protocols
UNSW Canberra
Authors:
Title:
Institution:
Fariba Abbasi Aghdam Meinagh, Emanuele Viterbo
Soft Decision Decoding of polar codes with large kernels
Monash University
Authors:
Title:
Institution:
Viduranga Wijekoon, Hoang Dau, Emanuele Viterbo
Soft Decision Decoding of Reed-Solomon Codes based on Non-binary Matrices
Monash University
Authors:
Title:
Institution:
Yizhou YANG, David Smith, Suranga Seneviratne
Deep Learning Channel Prediction for Transmit Power Control in Wireless Body Area Networks
ANU
Authors:
Title:
Institution:
Ziqi Chen; David Smith
Heterogeneous Random Access Optimization by Deep Reinforcement Learning
UNSW
Authors:
Title:
Institution:
Mohammad Rowshan and Emanuele Viterbo
Stepped List Decoding: A Memory-efficient and Low-complexity Approach
Monash University
Authors:
Title:
Institution:
Kameliya Kaneva, Neda Aboutorab, Sameh Sorour and Mark C Reed
Cross-Layer Offloading in Fog-RANs using Device Cooperation and Network Coding
UNSW
Authors:
Title:
Institution:
Jithin George, Phee Lep Yeoh, Brian Krongold
Relay-Energy Access Points for Internet-of-Things Wireless Energy Harvesting and Communications
University of Melbourne

Presentations of Invited Demos


Demo Presentation 1 (Dr Wibowo Hardjawana):

Title: Softwarising Real-time LTE Scheduler: Concept and Prototype

Abstract: The future cellular network will need to be softwarised in order to provide flexibility for handling numerous types of time-varying traffic with flexible requirements. Softwarisation allows operators to change the scheduler logic of an evolved NodeB (eNodeB) at the edge base station (BS) in real-time. Two types of scheduler architectures have been proposed in the literature: 1) a distributed non-programmable scheduler in which the underlying real-time scheduling logic cannot be programmed due to tight control by the eNodeB vendor at the edge base station, and 2) a centralised scheduler in which only non-real-time scheduling logic is programmable. In this presentation, we propose a distributed real-time softwarisation architecture for a long-term evolution (LTE) resource scheduler. The scheduling logic is written as a software independently of the underlying eNodeB and executed in real-time at the edge BS with the help of a scheduler agent. The proposed softwarisation architecture is validated in an over-the-air environment with commercial LTE devices and 3rd Generation Partnership Project (3GPP) standards-compliant setup.

Bio: WIBOWO HARDJAWANA (M’09) received the Ph.D. degree in electrical engineering from The University of Sydney, Australia, in 2009. From 1999 to 2005, he was with Singapore Telecom Ltd. He was an Australian Research Council Discovery Early Career Research Award Fellow from 2015-2018 and now Senior Lecturer at the School of Electrical and Information Engineering, The University of Sydney. His current research interests are in network softwarisation algorithms and protoypes development for wireless cellular networks.
Demo Presentation 2 (Dr Yixuan Xie):

Abstract: In this demo presentation, I will give an overview of massive random access schemes for machine-type communications and very high-speed channel codecs for ultra-reliable digital communication or data storage systems, which were implemented at UNSW Wireless Communications Lab. The implementation of random multiple access protocol is based on Coded Slotted ALOHA (CSA) schemes. To resolve packet collisions and improve the system throughput, the Successive Interference Cancellation (SIC) detection algorithm is implemented. We show a demo of this implementation of CSA on NI USRP-RIO platforms. In addition, I will also present the design and FPGA implementation of LDPC decoder for ultra-reliable high-speed storage and communication systems, such as Fiber-optical communications, Flash memory storage devices, and deep space communications, which require high-speed error correction decoding schemes and a bit-error rate of 10^-15 or lower. Finally, an introduction of millimeter wave system with maximum 3 Gbps datalink throughput is given, and over-the-air data and video transmissions are demonstrated using 28GHz radio heads.

Bio: Yixuan Xie received his Ph.D degree in Electrical Engineering from the University of New South Wales (UNSW), Australia in 2016. Since then, he has been focused on implementing and prototyping coding/communications schemes and algorithm as a postdoc research fellow. He is currently a professional engineer at the School of Electrical Engineering and Telecommunications,UNSW. His research interests include error control coding, digital communication systems, iterative detection/decoding methods and multiple access schemes. He collaboratively holds a number of international patents with Huawei China, and has published more than 20 journal articles and conference papers. He also served as a reviewer for multiple IEEE journals and conference proceedings.