103 research outputs found
Reconfigurable Intelligent Surfaces for Wireless Communications: Principles, Challenges, and Opportunities
Recently there has been a flurry of research on the use of reconfigurable
intelligent surfaces (RIS) in wireless networks to create smart radio
environments. In a smart radio environment, surfaces are capable of
manipulating the propagation of incident electromagnetic waves in a
programmable manner to actively alter the channel realization, which turns the
wireless channel into a controllable system block that can be optimized to
improve overall system performance. In this article, we provide a tutorial
overview of reconfigurable intelligent surfaces (RIS) for wireless
communications. We describe the working principles of reconfigurable
intelligent surfaces (RIS) and elaborate on different candidate implementations
using metasurfaces and reflectarrays. We discuss the channel models suitable
for both implementations and examine the feasibility of obtaining accurate
channel estimates. Furthermore, we discuss the aspects that differentiate RIS
optimization from precoding for traditional MIMO arrays highlighting both the
arising challenges and the potential opportunities associated with this
emerging technology. Finally, we present numerical results to illustrate the
power of an RIS in shaping the key properties of a MIMO channel.Comment: to appear in the IEEE Transactions on Cognitive Communications and
Networking (TCCN
Parallel QR decomposition in LTE-A systems
The QR Decomposition (QRD) of communication channel matrices is a fundamental
prerequisite to several detection schemes in Multiple-Input Multiple-Output
(MIMO) communication systems. Herein, the main feature of the QRD is to
transform the non-causal system into a causal system, where consequently
efficient detection algorithms based on the Successive Interference
Cancellation (SIC) or Sphere Decoder (SD) become possible. Also, QRD can be
used as a light but efficient antenna selection scheme. In this paper, we
address the study of the QRD methods and compare their efficiency in terms of
computational complexity and error rate performance. Moreover, a particular
attention is paid to the parallelism of the QRD algorithms since it reduces the
latency of the matrix factorization.Comment: The eleventh IEEE International Workshop on Signal Processing
Advances for Wireless Communications, 5 pages, 4 figures, 4 algorithms, 1
tabl
Increased Multiplexing Gain with Reconfigurable Surfaces: Simultaneous Channel Orthogonalization and Information Embedding
Reconfigurable surface (RS) has been shown to be an effective solution for
improving wireless communication links in general multi-user multiple-input
multiple-output (MU-MIMO) setting. Current research efforts have been largely
directed towards the study of reconfigurable intelligent surface (RIS), which
corresponds to an RS made of passive reconfigurable elements with only phase
shifting capabilities. RIS constitutes a cost- and energy- efficient solution
for increased beamforming gain since it allows to generate constructive
interference towards desired directions, e.g., towards a base station (BS).
However, in many situations, multiplexing gain may have greater impact on the
achievable transmission rates and number of simultaneously connected devices,
while RIS has only been able to achieve minor improvements in this aspect.
Recent work has proposed the use of alternative RS technologies, namely
amplitude-reconfigurable intelligent surface (ARIS) and fully-reconfigurable
intelligent surface (FRIS), to achieve perfect orthogonalization of MU-MIMO
channels, thus allowing for maximum multiplexing gain at reduced complexity. In
this work we consider the use of ARIS and FRIS for simultaneously
orthogonalizing a MU-MIMO channel, while embedding extra information in the
orthogonalized channel. We show that the resulting achievable rates allow for
full exploitation of the degrees of freedom in a MU-MIMO system with excess of
BS antennas.Comment: 6 pages, 2 figures, accepted at IEEE GLOBECOM 202
A Scalable VLSI Architecture for Soft-Input Soft-Output Depth-First Sphere Decoding
Multiple-input multiple-output (MIMO) wireless transmission imposes huge
challenges on the design of efficient hardware architectures for iterative
receivers. A major challenge is soft-input soft-output (SISO) MIMO demapping,
often approached by sphere decoding (SD). In this paper, we introduce the - to
our best knowledge - first VLSI architecture for SISO SD applying a single
tree-search approach. Compared with a soft-output-only base architecture
similar to the one proposed by Studer et al. in IEEE J-SAC 2008, the
architectural modifications for soft input still allow a one-node-per-cycle
execution. For a 4x4 16-QAM system, the area increases by 57% and the operating
frequency degrades by 34% only.Comment: Accepted for IEEE Transactions on Circuits and Systems II Express
Briefs, May 2010. This draft from April 2010 will not be updated any more.
Please refer to IEEE Xplore for the final version. *) The final publication
will appear with the modified title "A Scalable VLSI Architecture for
Soft-Input Soft-Output Single Tree-Search Sphere Decoding
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