GlobalSIP 2016:

Symposium on Transceivers and Signal Processing for 5G Wireless and mm-Wave Systems

Schedule

Keynote Speakers

DT5G-K1: Thomas L. Marzetta, Nokia Bell Labs

Massive MIMO: It Really Works!

Recent Massive MIMO experiments have convincingly demonstrated the soundness of the underlying concept. Massive MIMO is poised to deliver spectacular improvements over 4G wireless technologies.

Massive MIMO creates virtual parallel circuits, each occupying the full spectral bandwidth, between a multiplicity of single-antenna terminals and an array of individually controlled antennas. Area spectral efficiency improvements over 4G technologies may range from ten to one-thousand, depending on the mobility of the terminals. Other benefits include energy efficiency gains in excess of one-thousand, and simple and effective power control that yields uniformly great service throughout the cell.

Cellular deployment of Massive MIMO in the prime sub-5GHz bands will be both hugely beneficial and highly disruptive, requiring either new TDD spectrum, or the reassignment of existing FDD spectrum, and the replacement of all base station and user equipment. There are less disruptive, but still exciting, applications of Massive MIMO, including small cell backhaul and fixed wireless access to homes, for which there are no back compatibility issues.

DT5G-K2: Joe Cavallaro, Rice University

Algorithms, Architectures, and Testbeds for 5G Wireless Communication Systems

Wireless communication system concepts for 5G include a variety of advanced physical layer algorithms to provide high data rates and increased efficiency. Each of these algorithms provide different challenges for real-time performance based on the tradeoffs between computation, communication, and I/O bottlenecks and area, time, and power complexity. In particular, Massive MIMO systems can provide many benefits for both uplink detection and downlink beamforming as the number of base station antennas increases. Similarly, channel coding, such as LDPC, can support high data rates in many channel conditions. At the RF level, limited available spectrum is leading to noncontiguous channel allocations where digital pre-distortion (DPD) can be used to improve power amplifier efficiency. Each of these schemes impose complex system organization challenges in the interconnection of multiple RF transceivers with multiple memory and computation units with multiple data rates within the system. Parallel numerical methods can be applied to tradeoff computational complexity with minimal effect on error rate performance. Simulation acceleration environments can be used to provide thorough system performance analysis. In this talk, we will focus on design tools for high level synthesis (HLS) to capture and express parallelism in wireless algorithms. This also includes the mapping to GPU and multicore systems for high speed simulation. HLS can also be applied to FPGA and ASIC synthesis, however, there exist tradeoffs in area with flexibility and reuse of designs. Heterogeneous system architectures as expressed by Systems on Chip (SoC) attempt to address these system issues. The talk will conclude with a discussion of computation testbeds from supercomputers through desktop GPU to single board systems. The integration with radio testbeds from WARP and USRP to NI and Argos prototype massive MIMO systems will be explored.

DT5G-K3: Robert W. Heath, Jr., University of Texas at Austin

Signal Processing Challenges in Broadband mmWave

Millimeter wave is the future of cellular and local area networks. Though the main motivation for mmWave is large spectral channels, most signal processing work has focused on tractable narrowband signal models. In this talk I review the challenges associated with signal processing in broadband millimeter wave channels. Then I review recent developments on two important topics. First, I explain the design of hybrid precoding and combing algorithms, which use a mixture of frequency-flat analog and frequency-selective digital precoding and combining. Second, I show how to formulate the hybrid frequency selective channel estimation algorithm to exploiting sparsity in the delay and angular domains. The hybrid precoders and combiners can then be configured based on the channel estimates, to achieve high spectral efficiency in broadband MIMO channels.

Wireless communications networks and associated devices are currently under intensive research as cellular networks are moving from 3G/4G towards the 5G era. Significant technological advances are required to meet the demand for increased data rates, substantially reduced latencies, support for a massive number of simultaneous devices, increased energy efficiency, and QoS guarantees.

Some of the most promising approaches for meeting the new requirements include the adoption of cmWave and mmWave frequencies, cognitive radio and other intelligent and flexible methods for RF spectrum use, device centric network architecture, massive MIMO, cooperative network wide multipoint processing, core network virtualization and reconsideration of the data, control and management planes.

Meeting the 5G demands is tied to the computational platforms of base stations and devices on which the cellular network is built. Recent advances in computing solutions, such as heterogeneous, data parallel and reconfigurable platforms, together with technological advances in analog, mixed-signal and digital circuits provide the means for developing efficient, yet flexible computation platforms. At the same time, the constantly increasing complexity of wireless communications solutions and underlying processing platforms mandatorily requires advances in design methodologies, high-level programming languages and tools. Hence, development and innovation of concrete 5G solutions requires experts from both wireless communications, and design and implementation communities.

Submissions are welcome on topics including:

• Software-defined and cognitive radio
• Technologies, circuits and algorithms for mm-wave
• mm-wave access networks and mobile back/front-haul
• Sparse channel models and estimation for mm-waves
• Fast transceiver processing and A/D conversion technologies for mm-waves
• Heterogeneous and small cell networks
• Massive MIMO, particularly signal processing and hardware challenges
• Cloud radio access networks and their computation and design challenges
• Optimization of radio resource management solutions and algorithms
• Advanced solutions for flexible spectrum access, including full-duplex, flexible FDD and dynamic TDD
• Advanced solutions for low-latency communications
• Optimization of transceiver algorithms
• Signal processing solutions against RF imperfections
• Design and implementation of wireless transceiver functionalities on programmable heterogeneous and multicore platforms
• FPGA and VLSI implementations of wireless transceiver functionalities
• Design methodologies and tools for wireless transceiver design
• Algorithm design / optimization and implementation codesign

[Download the PDF Call for Papers]

Paper Submission

Prospective authors are invited to submit papers with up to four pages for technical content including figures and with one optional 5th page containing references only. Manuscripts should be original (not submitted/published anywhere else) and written in accordance with the standard IEEE double-column paper template. Submission is through the GlobalSIP website at http://2016.ieeeglobalsip.org/Papers.asp.

Organizing Committee

• Mikko Valkama Tampere University of Technology, Finland
• Yuan-Hao Huang National Tsing Huang University, Taiwan

Technical Committee Co-Chairs

• Markku Juntti, University of Oulu, Finland
• Jani Boutellier, Tampere University of Technology, Finland

Technical Program Committee

• Angeliki Alexiou, University of Piraeus, Greece
• Lauri Anttila, Tampere University of Technology, Finland
• Mats Bengtsson, KTH Royal Institute of Technology, Sweden
• Randall Berry, Northwestern University, United States
• Shuvra Bhattacharyya, University of Maryland, United States
• Andreas Burg, EPFL, Switzerland
• Danijela Cabric, University of California, Los Angeles, United States
• Joseph Cavallaro, Rice University, United States
• Ediz Cetin, University of New South Wales, Australia
• Chaitali Chakrabarti, Arizona State University, United States
• Chong-Yung Chi, National Tsing Hua University, Taiwan
• Giuseppe Destino, University of Oulu, Finland
• Octavia Dobre, Memorial University, Canada
• Thomas Eriksson, Chalmers University, Sweden
• Maksym Girnyk, Ericsson
• Martin Haardt, TU Ilmenau, Germany
• Janne Janhunen, University of Oulu, Finland
• Kimmo Kansanen, Norwegian University of Science and Technology, Norway
• Brian M. Kurkoski, Japan Advanced Institute of Science and Technology, Japan
• Charlotte Langlais, Telecom Bretagne, France
• Min Li, NXP Semiconductor
• Chunshu Li, Marvell
• Sellathurai Mathini, Heriot-Watt University, United Kingdom
• John McAllister, Queen's University Belfast, United Kingdom
• Chandra Murthy, University of California, San Diego, United States
• Maxime Pelcat, INSA Rennes, France
• Ana Isabel Perez, Universidad Politécnica de Madrid, Spain
• Sofie Pollin, KU Leuven, Belgium
• Nandana Rajatheva, University of Oulu, Finland
• Markku Renfors, Tampere University of Technology, Finland
• Taneli Riihonen, Aalto University, Finland
• Tapani Ristaniemi, University of Jyväskylä, Finland
• Farhana Sheikh, Intel
• Olli Silvén, University of Oulu, Finland
• Leonel Sousa, INESC-ID, Portugal
• Christoph Studer, Cornell University, United States
• Yang Sun, Qualcomm
• Himal Suraweera, University of Peradeniya, Sri Lanka
• Valtteri Tervo, University of Oulu, Finland
• Olav Tirkkonen, Aalto University, Finland
• LeNam Tran, Maynooth University, Ireland
• Pei-Yun Tsai, National Central University, Taiwan
• Antti Tölli, University of Oulu, Finland
• Wolfgang Utschick, TU Munich, Germany
• Jaap van de Beek, Luleå University of Technology, Sweden
• Zhongfeng Wang, Broadcom
• Johanna Vartiainen, University of Oulu, Finland
• Risto Wichman, Aalto University, Finland
• Sau-Hsuan Wu, National Chiao Tung University, Taiwan
• Gerhard Wunder, Fraunhofer Heinrich Hertz Institute, Germany
• Pengfei Xia, InterDigital
• Zhiyuan Yan, Lehigh University, United States
• Shingo Yoshizawa, Kitami Institute of Technology, Japan
• Haijun Zhang, University of British Columbia, Canada
• Xinmiao Zhang, Case Western Universitu, United States
• Zhengya Zhang, University of Michigan, United States
• Chuan Zhang, Southeast University, China