97 research outputs found
Sum-Rate Maximization of Uplink Rate Splitting Multiple Access (RSMA) Communication
In this paper, the problem of maximizing the wireless users' sum-rate for
uplink rate splitting multiple access (RSMA) communications is studied. In the
considered model, each user transmits a superposition of two messages to a base
station (BS) with separate transmit power and the BS uses a successive decoding
technique to decode the received messages. To maximize each user's transmission
rate, the users must adjust their transmit power and the BS must determine the
decoding order of the messages transmitted from the users to the BS. This
problem is formulated as a sum-rate maximization problem with proportional rate
constraints by adjusting the users' transmit power and the BS's decoding order.
However, since the decoding order variable in the optimization problem is
discrete, the original maximization problem with transmit power and decoding
order variables can be transformed into a problem with only the rate splitting
variable. Then, the optimal rate splitting of each user is determined. Given
the optimal rate splitting of each user and a decoding order, the optimal
transmit power of each user is calculated. Next, the optimal decoding order is
determined by an exhaustive search method. To further reduce the complexity of
the optimization algorithm used for sum-rate maximization in RSMA, a user
pairing based algorithm is introduced, which enables two users to use RSMA in
each pair and also enables the users in different pairs to be allocated with
orthogonal frequency. For comparisons, the optimal sum-rate maximizing
solutions with proportional rate constraints are obtained in closed form for
non-orthogonal multiple access (NOMA), frequency division multiple access
(FDMA), and time division multiple access (TDMA). Simulation results show that
RSMA can achieve up to 10.0\%, 22.2\%, and 83.7\% gains in terms of sum-rate
compared to NOMA, FDMA, and TDMA.Comment: 30 pages, 8 figure
Multiple Access in Aerial Networks: From Orthogonal and Non-Orthogonal to Rate-Splitting
Recently, interest on the utilization of unmanned aerial vehicles (UAVs) has
aroused. Specifically, UAVs can be used in cellular networks as aerial users
for delivery, surveillance, rescue search, or as an aerial base station (aBS)
for communication with ground users in remote uncovered areas or in dense
environments requiring prompt high capacity. Aiming to satisfy the high
requirements of wireless aerial networks, several multiple access techniques
have been investigated. In particular, space-division multiple access(SDMA) and
power-domain non-orthogonal multiple access (NOMA) present promising
multiplexing gains for aerial downlink and uplink. Nevertheless, these gains
are limited as they depend on the conditions of the environment. Hence, a
generalized scheme has been recently proposed, called rate-splitting multiple
access (RSMA), which is capable of achieving better spectral efficiency gains
compared to SDMA and NOMA. In this paper, we present a comprehensive survey of
key multiple access technologies adopted for aerial networks, where aBSs are
deployed to serve ground users. Since there have been only sporadic results
reported on the use of RSMA in aerial systems, we aim to extend the discussion
on this topic by modelling and analyzing the weighted sum-rate performance of a
two-user downlink network served by an RSMA-based aBS. Finally, related open
issues and future research directions are exposed.Comment: 16 pages, 6 figures, submitted to IEEE Journa
Rate-Splitting Multiple Access for Uplink Massive MIMO With Electromagnetic Exposure Constraints
Over the past few years, the prevalence of wireless devices has become one of
the essential sources of electromagnetic (EM) radiation to the public. Facing
with the swift development of wireless communications, people are skeptical
about the risks of long-term exposure to EM radiation. As EM exposure is
required to be restricted at user terminals, it is inefficient to blindly
decrease the transmit power, which leads to limited spectral efficiency and
energy efficiency (EE). Recently, rate-splitting multiple access (RSMA) has
been proposed as an effective way to provide higher wireless transmission
performance, which is a promising technology for future wireless
communications. To this end, we propose using RSMA to increase the EE of
massive MIMO uplink while limiting the EM exposure of users. In particularly,
we investigate the optimization of the transmit covariance matrices and
decoding order using statistical channel state information (CSI). The problem
is formulated as non-convex mixed integer program, which is in general
difficult to handle. We first propose a modified water-filling scheme to obtain
the transmit covariance matrices with fixed decoding order. Then, a greedy
approach is proposed to obtain the decoding permutation. Numerical results
verify the effectiveness of the proposed EM exposure-aware EE maximization
scheme for uplink RSMA.Comment: to appear in IEEE Journal on Selected Areas in Communication
Rate-Splitting Multiple Access for Short-Packet Uplink Communications: A Finite Blocklength Error Probability Analysis
In this letter, we investigate Rate-Splitting Multiple Access (RSMA) for an
uplink communication system with finite blocklength. Considering a two-user
Single-Input Single-Output (SISO) Multiple Access Channel (MAC), we study the
impact of Signal-to-Noise Ratio (SNR), blocklength, power allocation and target
rate on the error probability performance of RSMA where one user message is
split. We demonstrate that RSMA can improve the error probability performance
significantly compared to Non-Orthogonal Multiple Access (NOMA) and RSMA can
have a larger rate region than NOMA.Comment: 5 pages, 3 figure
Fairness Optimization of RSMA for Uplink Communication based on Intelligent Reflecting Surface
In this paper, we propose a rate-splitting multiple access (RSMA) scheme for
uplink wireless communication systems with intelligent reflecting surface (IRS)
aided. In the considered model, IRS is adopted to overcome power attenuation
caused by path loss. We construct a max-min fairness optimization problem to
obtain the resource allocation, including the receive beamforming at the base
station (BS) and phase-shift beamforming at IRS. We also introduce a successive
group decoding (SGD) algorithm at the receiver, which trades off the fairness
and complexity of decoding. In the simulation, the results show that the
proposed scheme has superiority in improving the fairness of uplink
communication.Comment: This paper has been accepted by Globecom 202
Rate-Splitting Multiple Access for 6G -- Part I: Principles, Applications and Future Works
This letter is the first part of a three-part tutorial focusing on
rate-splitting multiple access (RSMA) for 6G. As Part I of the tutorial, the
letter presents the basics of RSMA and its applications in light of 6G. To
begin with, we first delineate the design principle and basic transmission
frameworks of downlink and uplink RSMA. We then illustrate the applications of
RSMA for addressing the challenges of various potential enabling technologies
and use cases, consequently making it a promising next generation multiple
access (NGMA) scheme for future networks such as 6G and beyond. We briefly
discuss the challenges of RSMA and conclude the letter. In continuation of Part
I, we will focus on the interplay of RSMA with integrated sensing and
communication, and reconfigurable intelligent surfaces, respectively in Part II
and Part III of this tutorial
Low-complexity Resource Allocation for User Paired RSMA in Future 6G Wireless Networks
Rate-splitting multiple access (RSMA) uplink requires optimization of
decoding order and power allocation, while decoding order is a discrete
variable, and it is very complex to find the optimal decoding order if the
number of users is large enough. This letter proposes a low-complexity user
pairing-based resource allocation algorithm with the objective of minimizing
the maximum latency, which significantly reduces the computational complexity
and also achieves similar performance to unpaired uplink RSMA. A closed-form
expression for power and bandwidth allocation is first derived, and then a
bisection method is used to determine the optimal resource allocation. Finally,
the proposed algorithm is compared with unpaired RSMA, paired NOMA and unpaired
NOMA. The results demonstrate the effectiveness of the proposed algorithm
Transmission Scheme, Detection and Power Allocation for Uplink User Cooperation with NOMA and RSMA
In this paper, we propose two novel
cooperative-non-orthogonal-multiple-access (C-NOMA) and
cooperative-rate-splitting-multiple-access (C-RSMA) schemes for uplink user
cooperation. At the first mini-slot of these schemes, each user transmits its
signal and receives the transmitted signal of the other user in full-duplex
mode, and at the second mini-slot, each user relays the other user's message
with amplify-and-forward (AF) protocol. At both schemes, to achieve better
spectral efficiency, users transmit signals in the non-orthogonal mode in both
mini-slots. In C-RSMA, we also apply the rate-splitting method in which the
message of each user is divided into two streams. In the proposed detection
schemes for C-NOMA and C-RSMA, we apply a combination of
maximum-ratio-combining (MRC) and successive-interference-cancellation (SIC).
Then, we derive the achievable rates for C-NOMA and C-RSMA, and formulate two
optimization problems to maximize the minimum rate of two users by considering
the proportional fairness coefficient. We propose two power allocation
algorithms based on successive-convex-approximation (SCA) and
geometric-programming (GP) to solve these non-convex problems. Next, we derive
the asymptotic outage probability of the proposed C-NOMA and C-RSMA schemes,
and prove that they achieve diversity order of two. Finally, the
above-mentioned performance is confirmed by simulations.Comment: 32 pages, 13 figure
Machine Learning for Predictive Deployment of UAVs with Multiple Access
In this paper, a machine learning based deployment framework of unmanned
aerial vehicles (UAVs) is studied. In the considered model, UAVs are deployed
as flying base stations (BS) to offload heavy traffic from ground BSs. Due to
time-varying traffic distribution, a long short-term memory (LSTM) based
prediction algorithm is introduced to predict the future cellular traffic. To
predict the user service distribution, a KEG algorithm, which is a joint
K-means and expectation maximization (EM) algorithm based on Gaussian mixture
model (GMM), is proposed for determining the service area of each UAV. Based on
the predicted traffic, the optimal UAV positions are derived and three
multi-access techniques are compared so as to minimize the total transmit
power. Simulation results show that the proposed method can reduce up to 24\%
of the total power consumption compared to the conventional method without
traffic prediction. Besides, rate splitting multiple access (RSMA) has the
lower required transmit power compared to frequency domain multiple access
(FDMA) and time domain multiple access (TDMA)
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