96 research outputs found
Low Complexity WMMSE Power Allocation In NOMA-FD Systems
In this paper we study the problem of power and channel allocation with the
objective of maximizing the system sum-rate for multicarrier non-orthogonal
multiple access (NOMA) full duplex (FD) systems. Such an allocation problem is
non-convex and, thus, with the goal of designing a low complexity solution, we
propose a scheme based on the minimization of the weighted mean square error,
which achieves performance reasonably close to the optimum and allows to
clearly outperforms a conventional orthogonal multiple access approach.
Numerical results assess the effectiveness of our algorithm.Comment: 5 pages conference paper, 3 figures. Submitted on ICASSP 202
Rainfall Map from Attenuation Data Fusion of Satellite Broadcast and Commercial Microwave Links
The demand for accurate rainfall rate maps is growing ever more. This paper proposes a novel algorithm to estimate the rainfall rate map from the attenuation measurements coming from both broadcast satellite links (BSLs) and commercial microwave links (CMLs). The approach we pursue is based on an iterative procedure which extends the well-known GMZ algorithm to fuse the attenuation data coming from different links in a three-dimensional scenario, while also accounting for the virga phenomenon as a rain vertical attenuation model. We experimentally prove the convergence of the procedures, showing how the estimation error decreases for every iteration. The numerical results show that adding the BSL links to a pre-existent CML network boosts the accuracy performance of the estimated rainfall map, improving up to 50% the correlation metrics. Moreover, our algorithm is shown to be robust to errors concerning the virga parametrization, proving the possibility of obtaining good estimation performance without the need for precise and real-time estimation of the virga parameters
Deep Reinforcement Learning for URLLC data management on top of scheduled eMBB traffic
With the advent of 5G and the research into beyond 5G (B5G) networks, a novel
and very relevant research issue is how to manage the coexistence of different
types of traffic, each with very stringent but completely different
requirements. In this paper we propose a deep reinforcement learning (DRL)
algorithm to slice the available physical layer resources between
ultra-reliable low-latency communications (URLLC) and enhanced Mobile BroadBand
(eMBB) traffic. Specifically, in our setting the time-frequency resource grid
is fully occupied by eMBB traffic and we train the DRL agent to employ proximal
policy optimization (PPO), a state-of-the-art DRL algorithm, to dynamically
allocate the incoming URLLC traffic by puncturing eMBB codewords. Assuming that
each eMBB codeword can tolerate a certain limited amount of puncturing beyond
which is in outage, we show that the policy devised by the DRL agent never
violates the latency requirement of URLLC traffic and, at the same time,
manages to keep the number of eMBB codewords in outage at minimum levels, when
compared to other state-of-the-art schemes.Comment: This work has been submitted to the IEEE for possible publication.
Copyright may be transferred without notice, after which this version may no
longer be accessibl
Hybrid Message Passing Algorithm for Downlink FDD Massive MIMO-OFDM Channel Estimation
The design of message passing algorithms on factor graphs has been proven to
be an effective manner to implement channel estimation in wireless
communication systems. In Bayesian approaches, a prior probability model that
accurately matches the channel characteristics can effectively improve
estimation performance. In this work, we study the channel estimation problem
in a frequency division duplexing (FDD) downlink massive multiple-input
multiple-output (MIMO) orthogonal frequency division multiplexing (OFDM)
system. As the prior probability, we propose the Markov chain two-state
Gaussian mixture with large variance difference (TSGM-LVD) model to exploit the
structured sparsity in the angle-frequency domain of the massive MIMO-OFDM
channel. In addition, we present a new method to derive the hybrid message
passing (HMP) rule, which can calculate the message with mixed linear and
non-linear model. To the best of the authors' knowledge, we are the first to
apply the HMP rule to practical communication systems, designing the
HMP-TSGM-LVD algorithm under the structured turbo-compressed sensing (STCS)
framework. Simulation results demonstrate that the proposed HMP-TSGM-LVD
algorithm converges faster and outperforms its counterparts under a wide range
of simulation settings
A Random Access Protocol for RIS-Aided Wireless Communications
Reconfigurable intelligent surfaces (RISs) are arrays of passive elements
that can control the reflection of the incident electromagnetic waves. While
RIS are particularly useful to avoid blockages, the protocol aspects for their
implementation have been largely overlooked. In this paper, we devise a random
access protocol for a RIS-assisted wireless communication setting. Rather than
tailoring RIS reflections to meet the positions of users equipment (UEs), our
protocol relies on a finite set of RIS configurations designed to cover the
area of interest. The protocol is comprised of a downlink training phase
followed by an uplink access phase. During these phases, a base station (BS)
controls the RIS to sweep over its configurations. The UEs then receive
training signals to measure the channel quality with the different RIS
configurations and refine their access policies. Numerical results show that
our protocol increases the average number of successful access attempts;
however, at the expense of increased access delay due to the realization of a
training period. Promising results are further observed in scenarios with a
high access load.Comment: 5 pages, 2 figures, conference versio
A Framework for Control Channels Applied to Reconfigurable Intelligent Surfaces
The research on Reconfigurable Intelligent Surfaces (RISs) has dominantly
been focused on physical-layer aspects and analyses of the achievable
adaptation of the propagation environment. Compared to that, the questions
related to link/MAC protocol and system-level integration of RISs have received
much less attention. This paper addresses the problem of designing and
analyzing control/signaling procedures, which are necessary for the integration
of RISs as a new type of network element within the overall wireless
infrastructure. We build a general model for designing control channels along
two dimensions: i) allocated bandwidth (in-band and out-of band) and ii) rate
selection (multiplexing or diversity). Specifically, the second dimension
results in two transmission schemes, one based on channel estimation and the
subsequent adapted RIS configuration, while the other is based on sweeping
through predefined RIS phase profiles. The paper analyzes the performance of
the control channel in multiple communication setups, obtained as combinations
of the aforementioned dimensions. While necessarily simplified, our analysis
reveals the basic trade-offs in designing control channels and the associated
communication algorithms. Perhaps the main value of this work is to serve as a
framework for subsequent design and analysis of various system-level aspects
related to the RIS technology.Comment: Submitted to IEEE TWC, the copyright may be transferred without
further notic
Random Access Protocol with Channel Oracle Enabled by a Reconfigurable Intelligent Surface
The widespread adoption of Reconfigurable Intelligent Surfaces (RISs) in
future practical wireless systems is critically dependent on the design and
implementation of efficient access protocols, an issue that has received less
attention in the research literature. In this paper, we propose a grant-free
random access (RA) protocol for a RIS-assisted wireless communication setting,
where a massive number of users' equipment (UEs) try to access an access point
(AP). The proposed protocol relies on a channel oracle, which enables the UEs
to infer the best RIS configurations that provide opportunistic access to UEs.
The inference is based on a model created during a training phase with a
greatly reduced set of RIS configurations. Specifically, we consider a system
whose operation is divided into three blocks: i) a downlink training block,
which trains the model used by the oracle, ii) an uplink access block, where
the oracle infers the best access slots, and iii) a downlink acknowledgment
block, which provides feedback to the UEs that were successfully decoded by the
AP during access. Numerical results show that the proper integration of the RIS
into the protocol design is able to increase the expected end-to-end throughput
by approximately 40% regarding the regular repetition slotted ALOHA protocol.Comment: 30 pages, 7 figures, journal pape
An Orchestration Framework for Open System Models of Reconfigurable Intelligent Surfaces
To obviate the control of reflective intelligent surfaces (RISs) and the
related control overhead, recent works envisioned autonomous and
self-configuring RISs that do not need explicit use of control channels.
Instead, these devices, named hybrid RISs (HRISs), are equipped with receiving
radio-frequency (RF) chains and can perform sensing operations to act
independently and in parallel to the other network entities. A natural problem
then emerges: as the HRIS operates concurrently with the communication
protocols, how should its operation modes be scheduled in time such that it
helps the network while minimizing any undesirable effects? In this paper, we
propose an orchestration framework that answers this question revealing an
engineering trade-off, called the self-configuring trade-off, that
characterizes the applicability of self-configuring HRISs under the
consideration of massive multiple-input multiple-output (mMIMO) networks. We
evaluate our proposed framework considering two different HRIS hardware
architectures, the power- and signal-based HRISs that differ in their hardware
complexity. The numerical results show that the self-configuring HRIS can offer
significant performance gains when adopting our framework.Comment: 31 pages, 7 figures, submitted to an IEEE journa
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