4 research outputs found
RISMA: Reconfigurable Intelligent Surfaces Enabling Beamforming for IoT Massive Access
Massive access for Internet-of-Things (IoT) in beyond 5G networks represents
a daunting challenge for conventional bandwidth-limited technologies.
Millimeter-wave technologies (mmWave)---which provide large chunks of bandwidth
at the cost of more complex wireless processors in harsher radio
environments---is a promising alternative to accommodate massive IoT but its
cost and power requirements are an obstacle for wide adoption in practice. In
this context, meta-materials arise as a key innovation enabler to address this
challenge by Re-configurable Intelligent Surfaces (RISs). In this paper we take
on the challenge and study a beyond 5G scenario consisting of a multi-antenna
base station (BS) serving a large set of single-antenna user equipments (UEs)
with the aid of RISs to cope with non-line-of-sight paths. Specifically, we
build a mathematical framework to jointly optimize the precoding strategy of
the BS and the RIS parameters in order to minimize the system sum mean squared
error (SMSE). This novel approach reveals convenient properties used to design
two algorithms, RISMA and Lo-RISMA, which are able to either find simple and
efficient solutions to our problem (the former) or accommodate practical
constraints with low-resolution RISs (the latter). Numerical results show that
our algorithms outperform conventional benchmarks that do not employ RIS (even
with low-resolution meta-surfaces) with gains that span from 20% to 120% in sum
rate performance.Comment: Accepted and to appear in IEEE Journal on Selected Areas in
Communications, Special Issue on Massive Access for 5G and Beyon
Intelligent Omni-Surface: Ubiquitous Wireless Transmission by Reflective-Transmissive Metasurface
Intelligent reflecting surface (IRS), which is capable to adjust propagation
conditions by controlling phase shifts of the reflected waves that impinge on
the surface, has been widely analyzed for enhancing the performance of wireless
systems. However, the reflective properties of widely studied IRSs restrict the
service coverage to only one side of the surface. In this paper, to extend the
wireless coverage of communication systems, we introduce the concept of
intelligent omni-surface (IOS)-assisted communication. More precisely, IOS is
an important instance of reconfigurable intelligent surface (RIS) that is
capable to provide service coverage to the mobile users (MUs) in a reflective
and a transmissive manner. We consider a downlink IOS-assisted communication
system, where a multi-antenna small base station (SBS) and an IOS perform
beamforming jointly, to improve the received power of multiple MUs on both
sides of the IOS, through different reflective/transmissive channels. To
maximize the sum-rate, we formulate a joint IOS phase shift design and SBS
beamforming optimization problem, and propose an iterative algorithm to solve
the resulting non-convex program efficiently. Both theoretical analysis and
simulation results show that an IOS significantly extends the service coverage
of the SBS when compared to an IRS
Fairness-Oriented Multiple RISs-Aided MmWave Transmission: Stochastic Optimization Approaches
In millimeter wave (mmWave) systems, it is challenging to ensure the reliable
connectivity of communications due to its sensitivity to the presence of
blockages. In order to improve the robustness of the mmWave system under the
presence of the random blockages, multiple reconfigurable intelligent surfaces
(RISs) are deployed to enhance the spatial diversity gain, and robust
beamforming is then designed based on a stochastic optimization for minimizing
the maximum outage probability among multiple users to ensure the fairness.
Under the stochastic optimization framework, we adopt the stochastic
majorization--minimization (SMM) method and the stochastic successive convex
approximation (SSCA) method to construct deterministic surrogate problems at
each iteration for new channel realizations, and obtain the closed-form
solutions of the precoding matrix at the base station (BS) and the passive
beamforming vectors at the RISs. Both stochastic optimization methods have been
proved to converge to the set of stationary points of the original stochastic
problems. Finally, simulation results show that the proposed robust beamforming
in the RIS-aided system can effectively compensate for the performance loss
caused by the presence of the random blockages, especially at high blockage
probability, compared with the benchmark solutions.Comment: Keywords: Reconfigurable intelligent surface (RIS), intelligent
reflecting surface (IRS
Reconfigurable Intelligent Surface-Assisted MAC for Wireless Networks: Protocol Design, Analysis, and Optimization
Reconfigurable intelligent surface (RIS) is a promising reflective radio
technology for improving the coverage and rate of future wireless systems by
reconfiguring the wireless propagation environment. The current work mainly
focuses on the physical layer design of RIS. However, enabling multiple devices
to communicate with the assistance of RIS is a crucial challenging problem.
Motivated by this, we explore RIS-assisted communications at the medium access
control (MAC) layer and propose an RIS-assisted MAC framework. In particular,
RISassisted transmissions are implemented by pre-negotiation and a
multi-dimension reservation (MDR) scheme. Based on this, we investigate
RIS-assisted single-channel multi-user (SCMU) communications. Wherein the RIS
regarded as a whole unity can be reserved by one user to support the multiple
data transmissions, thus achieving high efficient RIS-assisted connections at
the user. Moreover, under frequency-selective channels, implementing the MDR
scheme on the RIS group division, RISassisted multi-channel multi-user (MCMU)
communications are further explored to improve the service efficiency of the
RIS and decrease the computation complexity. Besides, a Markov chain is built
based on the proposed RIS-assisted MAC framework to analyze the system
performance of SCMU/MCMU. Then the optimization problem is formulated to
maximize the overall system capacity of SCMU/MCMU with energy-efficient
constraint. The performance evaluations demonstrate the feasibility and
effectiveness of eac