584 research outputs found
5G and beyond networks
This chapter investigates the Network Layer aspects that will characterize the merger of the cellular paradigm and the IoT architectures, in the context of the evolution towards 5G-and-beyond, including some promising emerging services as Unmanned Aerial Vehicles or Base Stations, and V2X communications
Massive MIMO is a Reality -- What is Next? Five Promising Research Directions for Antenna Arrays
Massive MIMO (multiple-input multiple-output) is no longer a "wild" or
"promising" concept for future cellular networks - in 2018 it became a reality.
Base stations (BSs) with 64 fully digital transceiver chains were commercially
deployed in several countries, the key ingredients of Massive MIMO have made it
into the 5G standard, the signal processing methods required to achieve
unprecedented spectral efficiency have been developed, and the limitation due
to pilot contamination has been resolved. Even the development of fully digital
Massive MIMO arrays for mmWave frequencies - once viewed prohibitively
complicated and costly - is well underway. In a few years, Massive MIMO with
fully digital transceivers will be a mainstream feature at both sub-6 GHz and
mmWave frequencies. In this paper, we explain how the first chapter of the
Massive MIMO research saga has come to an end, while the story has just begun.
The coming wide-scale deployment of BSs with massive antenna arrays opens the
door to a brand new world where spatial processing capabilities are
omnipresent. In addition to mobile broadband services, the antennas can be used
for other communication applications, such as low-power machine-type or
ultra-reliable communications, as well as non-communication applications such
as radar, sensing and positioning. We outline five new Massive MIMO related
research directions: Extremely large aperture arrays, Holographic Massive MIMO,
Six-dimensional positioning, Large-scale MIMO radar, and Intelligent Massive
MIMO.Comment: 20 pages, 9 figures, submitted to Digital Signal Processin
LaSR: A Supple Multi-Connectivity Scheduler for Multi-RAT OFDMA Systems
Network densification over space and spectrum is expected to be key to enabling the requirements of next generation mobile systems. The pitfall is that radio resource allocation becomes substantially more complex. In this paper we propose LaSR, a practical multi-connectivity scheduler for OFDMA-based multi-RAT systems. LaSR makes optimal discrete control actions by solving a sequence of simple optimization problems that do not require prior information of traffic patterns. In marked contrast to previous work, the flexibility of our approach allows us to construct scheduling policies that achieve a good balance between system cost and utility satisfaction, while jointly operate across heterogeneous RATs, accommodate real-system requirements, and guarantee system stability. Examples of system requirements considered in this paper include (but are not limited to): constraints on how scheduling data can be encoded onto signaling protocols (e.g. LTE’s DCI), delays when turning on/off radio units, or on/off cycles when using unlicensed spectrum. We evaluate our scheduler via a thorough simulation campaign in a variety of scenarios with e.g. mobile users, RATs using unlicensed spectrum (using a duty cycle access mechanism), imperfect queue state information, and constrained signaling protocol.The authors would like to thank the Spanish Government (Ministerio de EconomĂa y Competitividad, Fondo Europeo de Desarrollo Regional, FEDER) for its support through the project ADVICE (TEC2015-71329-C2-1-R) and 5G-Transformer Project (Grant 761536)
LaSR: a supple multi-connectivity scheduler for multi-RAT OFDMA systems
Network densification over space and spectrum is expected to be key to enabling the requirements of next generation mobile systems. The pitfall is that radio resource allocation becomes substantially more complex. In this paper we propose LaSR, a practical multi-connectivity scheduler for OFDMA-based multi-RAT systems. LaSR makes optimal discrete control actions by solving a sequence of simple optimization problems that do not require prior information of traffic patterns. In marked contrast to previous work, the flexibility of our approach allows us to construct scheduling policies that achieve a good balance between system cost and utility satisfaction, while jointly operate across heterogeneous RATs, accommodate real-system requirements, and guarantee system stability. Examples of system requirements considered in this paper include (but are not limited to): constraints on how scheduling data can be encoded onto signaling protocols (e.g. LTE's DCI), delays when turning on/off radio units, or on/off cycles when using unlicensed spectrum. We evaluate our scheduler via a thorough simulation campaign in a variety of scenarios with e.g. mobile users, RATs using unlicensed spectrum (using a duty cycle access mechanism), imperfect queue state information, and constrained signaling protocol.The authors would like to thank the Spanish Government (Ministerio de EconomĂa y Competitividad, Fondo Europeo de Desarrollo Regional, FEDER) for its support through the project ADVICE (TEC2015-71329-C2-1-R) and 5G-Transformer Project (Grant 761536)
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