115 research outputs found
V2X Meets NOMA: Non-Orthogonal Multiple Access for 5G Enabled Vehicular Networks
Benefited from the widely deployed infrastructure, the LTE network has
recently been considered as a promising candidate to support the
vehicle-to-everything (V2X) services. However, with a massive number of devices
accessing the V2X network in the future, the conventional OFDM-based LTE
network faces the congestion issues due to its low efficiency of orthogonal
access, resulting in significant access delay and posing a great challenge
especially to safety-critical applications. The non-orthogonal multiple access
(NOMA) technique has been well recognized as an effective solution for the
future 5G cellular networks to provide broadband communications and massive
connectivity. In this article, we investigate the applicability of NOMA in
supporting cellular V2X services to achieve low latency and high reliability.
Starting with a basic V2X unicast system, a novel NOMA-based scheme is proposed
to tackle the technical hurdles in designing high spectral efficient scheduling
and resource allocation schemes in the ultra dense topology. We then extend it
to a more general V2X broadcasting system. Other NOMA-based extended V2X
applications and some open issues are also discussed.Comment: Accepted by IEEE Wireless Communications Magazin
Resource Allocation for Downlink NOMA Systems: Key Techniques and Open Issues
This article presents advances in resource allocation (RA) for downlink
non-orthogonal multiple access (NOMA) systems, focusing on user pairing (UP)
and power allocation (PA) algorithms. The former pairs the users to obtain the
high capacity gain by exploiting the channel gain difference between the users,
while the later allocates power to users in each cluster to balance system
throughput and user fairness. Additionally, the article introduces the concept
of cluster fairness and proposes the divideand- next largest difference-based
UP algorithm to distribute the capacity gain among the NOMA clusters in a
controlled manner. Furthermore, performance comparison between multiple-input
multiple-output NOMA (MIMO-NOMA) and MIMO-OMA is conducted when users have
pre-defined quality of service. Simulation results are presented, which
validate the advantages of NOMA over OMA. Finally, the article provides avenues
for further research on RA for downlink NOMA.Comment: 5G, NOMA, Resource allocation, User pairing, Power allocatio
Multi-Beam NOMA for Hybrid mmWave Systems
In this paper, we propose a multi-beam non-orthogonal multiple access (NOMA)
scheme for hybrid millimeter wave (mmWave) systems and study its resource
allocation. A beam splitting technique is designed to generate multiple analog
beams to serve multiple users for NOMA transmission. Compared to conventional
mmWave orthogonal multiple access (mmWave-OMA) schemes, the proposed scheme can
serve more than one user on each radio frequency (RF) chain. Besides, in
contrast to the recently proposed single-beam mmWave-NOMA scheme which can only
serve multiple NOMA users within the same beam, the proposed scheme can perform
NOMA transmission for the users with an arbitrary angle-of-departure (AOD)
distribution. This provides a higher flexibility for applying NOMA in mmWave
communications and thus can efficiently exploit the potential multi-user
diversity. Then, we design a suboptimal two-stage resource allocation for
maximizing the system sum-rate. In the first stage, assuming that only analog
beamforming is available, a user grouping and antenna allocation algorithm is
proposed to maximize the conditional system sum-rate based on the coalition
formation game theory. In the second stage, with the zero-forcing (ZF) digital
precoder, a suboptimal solution is devised to solve a non-convex power
allocation optimization problem for the maximization of the system sum-rate
which takes into account the quality of service (QoS) constraint. Simulation
results show that our designed resource allocation can achieve a
close-to-optimal performance in each stage. In addition, we demonstrate that
the proposed multi-beam mmWave-NOMA scheme offers a higher spectral efficiency
than that of the single-beam mmWave-NOMA and the mmWave-OMA schemes.Comment: Submitted for possible journal publicatio
Data-Driven Random Access Optimization in Multi-Cell IoT Networks with NOMA
Non-orthogonal multiple access (NOMA) is a key technology to enable massive
machine type communications (mMTC) in 5G networks and beyond. In this paper,
NOMA is applied to improve the random access efficiency in high-density
spatially-distributed multi-cell wireless IoT networks, where IoT devices
contend for accessing the shared wireless channel using an adaptive
p-persistent slotted Aloha protocol. To enable a capacity-optimal network, a
novel formulation of random channel access management is proposed, in which the
transmission probability of each IoT device is tuned to maximize the geometric
mean of users' expected capacity. It is shown that the network optimization
objective is high dimensional and mathematically intractable, yet it admits
favourable mathematical properties that enable the design of efficient
data-driven algorithmic solutions which do not require a priori knowledge of
the channel model or network topology. A centralized model-based algorithm and
a scalable distributed model-free algorithm, are proposed to optimally tune the
transmission probabilities of IoT devices and attain the maximum capacity. The
convergence of the proposed algorithms to the optimal solution is further
established based on convex optimization and game-theoretic analysis. Extensive
simulations demonstrate the merits of the novel formulation and the efficacy of
the proposed algorithms.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
Secure Communications in NOMA System: Subcarrier Assignment and Power Allocation
Secure communication is a promising technology for wireless networks because
it ensures secure transmission of information. In this paper, we investigate
the joint subcarrier (SC) assignment and power allocation problem for
non-orthogonal multiple access (NOMA) amplify-and-forward two-way relay
wireless networks, in the presence of eavesdroppers. By exploiting cooperative
jamming (CJ) to enhance the security of the communication link, we aim to
maximize the achievable secrecy energy efficiency by jointly designing the SC
assignment, user pair scheduling and power allocation. Assuming the perfect
knowledge of the channel state information (CSI) at the relay station, we
propose a low-complexity subcarrier assignment scheme (SCAS-1), which is
equivalent to many-to-many matching games, and then SCAS-2 is formulated as a
secrecy energy efficiency maximization problem. The secure power allocation
problem is modeled as a convex geometric programming problem, and then solved
by interior point methods. Simulation results demonstrate that the
effectiveness of the proposed SSPA algorithms under scenarios of using and not
using CJ, respectively
Enhanced Energy-Efficient Downlink Resource Allocation in Green Non-Orthogonal Multiple Access Systems
Despite numerous advantages, non-orthogonal multiple access (NOMA) technique
can bring additional interference for the neighboring ultra-dense networks if
the power consumption of the system is not properly optimized. While targeting
on the green communication concept, in this paper, we propose an
energy-efficient downlink resource allocation scheme for a NOMA-equipped
cellular network. The objective of this work is to allocate subchannels and
power of the base station among the users so that the overall energy efficiency
is maximized. Since this problem is NP-hard, we attempt to find an elegant
solution with reasonable complexity that provides good performance for some
realistic applications. To this end, we decompose the problem into a subchannel
allocation subproblem followed by a power loading subproblem that allocates
power to each user's data stream on each of its allocated subchannels. We first
employ a many-to-many matching model under the assumption of uniform power
loading in order to obtain the solution of the first subproblem with reasonable
performance. Once the the subchannel-user mapping information is known from the
first solution, we propose a geometric programming (GP)-based power loading
scheme upon approximating the energy efficiency of the system by a ratio of two
posynomials. The techniques adopted for these subproblems better exploit the
available multi-user diversity compared to the techniques used in an earlier
work. Having observed the computational overhead of the GP-based power loading
scheme, we also propose a suboptimal computationally-efficient algorithm for
the power loading subproblem with a polynomial time complexity that provides
reasonably good performance. Extensive simulation has been conducted to verify
that our proposed solution schemes always outperform the existing work while
consuming much less power at the base station.Comment: 29 pages (Accepted
Resource Allocation for Device-to-Device Communications in Multi-Cell Multi-Band Heterogeneous Cellular Networks
Heterogeneous cellular networks (HCNs) with millimeter wave (mm-wave)
communications are considered as a promising technology for the fifth
generation mobile networks. Mm-wave has the potential to provide multiple
gigabit data rate due to the broad spectrum. Unfortunately, additional free
space path loss is also caused by the high carrier frequency. On the other
hand, mm-wave signals are sensitive to obstacles and more vulnerable to
blocking effects. To address this issue, highly directional narrow beams are
utilized in mm-wave networks. Additionally, device-to-device (D2D) users make
full use of their proximity and share uplink spectrum resources in HCNs to
increase the spectrum efficiency and network capacity. Towards the caused
complex interferences, the combination of D2D-enabled HCNs with small cells
densely deployed and mm-wave communications poses a big challenge to the
resource allocation problems. In this paper, we formulate the optimization
problem of D2D communication spectrum resource allocation among multiple
micro-wave bands and multiple mm-wave bands in HCNs. Then, considering the
totally different propagation conditions on the two bands, a heuristic
algorithm is proposed to maximize the system transmission rate and approximate
the solutions with sufficient accuracies. Compared with other practical
schemes, we carry out extensive simulations with different system parameters,
and demonstrate the superior performance of the proposed scheme. In addition,
the optimality and complexity are simulated to further verify effectiveness and
efficiency.Comment: 13 pages, 11 figures, IEEE Transactions on Vehicular Technolog
Intelligent Link Adaptation for Grant-Free Access Cellular Networks: A Distributed Deep Reinforcement Learning Approach
With the continuous growth of machine-type devices (MTDs), it is expected
that massive machine-type communication (mMTC) will be the dominant form of
traffic in future wireless networks. Applications based on this technology,
have fundamentally different traffic characteristics from human-to-human (H2H)
communication, which involves a relatively small number of devices transmitting
large packets consistently. Conversely, in mMTC applications, a very large
number of MTDs transmit small packets sporadically. Therefore, conventional
grant-based access schemes commonly adopted for H2H service, are not suitable
for mMTC, as they incur in a large overhead associated with the channel request
procedure. We propose three grant-free distributed optimization architectures
that are able to significantly minimize the average power consumption of the
network. The problem of physical layer (PHY) and medium access control (MAC)
optimization in grant-free random access transmission is is modeled as a
partially observable stochastic game (POSG) aimed at minimizing the average
transmit power under a per-device delay constraint. The results show that the
proposed architectures are able to achieve significantly less average latency
than a baseline, while spending less power. Moreover, the proposed
architectures are more robust than the baseline, as they present less variance
in the performance for different system realizations.Comment: 14 pages, 8 Figure
Sum-Rate Maximization for UAV-assisted Visible Light Communications using NOMA: Swarm Intelligence meets Machine Learning
As the integration of unmanned aerial vehicles (UAVs) into visible light
communications (VLC) can offer many benefits for massive-connectivity
applications and services in 5G and beyond, this work considers a UAV-assisted
VLC using non-orthogonal multiple-access. More specifically, we formulate a
joint problem of power allocation and UAV's placement to maximize the sum rate
of all users, subject to constraints on power allocation, quality of service of
users, and UAV's position. Since the problem is non-convex and NP-hard in
general, it is difficult to be solved optimally. Moreover, the problem is not
easy to be solved by conventional approaches, e.g., coordinate descent
algorithms, due to channel modeling in VLC. Therefore, we propose using harris
hawks optimization (HHO) algorithm to solve the formulated problem and obtain
an efficient solution. We then use the HHO algorithm together with artificial
neural networks to propose a design which can be used in real-time applications
and avoid falling into the "local minima" trap in conventional trainers.
Numerical results are provided to verify the effectiveness of the proposed
algorithm and further demonstrate that the proposed algorithm/HHO trainer is
superior to several alternative schemes and existing metaheuristic algorithms.Comment: Published in IEEE Internet of Things Journal (IoTJ) 202
- …