3 research outputs found
A Low-Complexity Framework for Joint User Pairing and Power Control for Cooperative NOMA in 5G and Beyond Cellular Networks
This paper investigates the performance of cooperative non-orthogonal
multiple access (C-NOMA) in a cellular downlink system. The system model
consists of a base station (BS) serving multiple users, where users with good
channel quality can assist the transmissions between the BS and users with poor
channel quality through either half-duplex (HD) or full-duplex (FD)
device-to-device (D2D) communications. We formulate and solve a novel
optimization problem that jointly determines the optimal D2D user pairing and
the optimal power control scheme, where the objective is maximizing the
achievable sum rate of the whole system while guaranteeing a certain quality of
service (QoS) for all users. The formulated problem is a mixed-integer
non-linear program (MINLP) which is generally NPhard. To overcome this issue,
we reconstruct the original problem into a bi-level optimization problem that
can be decomposed into two sub-problems to be solved independently. The outer
problem is a linear assignment problem which can be efficiently handled by the
well-known Hungarian method. The inner problem is still a non-convex
optimization problem for which finding the optimal solution is challenging.
However, we derive the optimal power control policies for both the HD and the
FD schemes in closedform expressions, which makes the computational complexity
of the inner problems polynomial for every possible pairing configurations.
These findings solve ultimately the original MILNP in a timely manner that
makes it suitable for real-time and low latency applications. Our simulation
results show that the proposed framework outperforms a variety of proposed
schemes in the literature and that it can obtain the optimal pairing and power
control policies for a network with 100 users in a negligible computational
time
Performance Analysis and Optimization of NOMA with HARQ for Short Packet Communications in Massive IoT
In this paper, we consider the massive non-orthogonal multiple access (NOMA)
with hybrid automatic repeat request (HARQ) for short packet communications. To
reduce the latency, each user can perform one re-transmission provided that the
previous packet was not decoded successfully. The system performance is
evaluated for both coordinated and uncoordinated transmissions. We first
develop a Markov model (MM) to analyze the system dynamics and characterize the
packet error rate (PER) and throughput of each user in the coordinated
scenario. The power levels are then optimized for two scenarios, including the
power constrained and reliability constrained scenarios. A simple yet efficient
dynamic cell planning is also designed for the uncoordinated scenario.
Numerical results show that both coordinated and uncoordinated NOMA-HARQ with a
limited number of retransmissions can achieve the desired level of reliability
with the guaranteed latency using a proper power control strategy. Results also
show that NOMA-HARQ achieves a higher throughput compared to the orthogonal
multiple access scheme with HARQ under the same average received power
constraint at the base station
Reconfigurable Intelligent Surface Enabled Full-Duplex/Half-Duplex Cooperative Non-Orthogonal Multiple Access
This paper investigates the downlink transmission of reconfigurable
intelligent surface (RIS)-aided cooperative non-orthogonal-multiple-access
(C-NOMA), where both half-duplex (HD) and full-duplex (FD) relaying modes are
considered. The system model consists of one base station (BS), two users and
one RIS. The goal is to minimize the total transmit power at both the BS and at
the user-cooperating relay for each relaying mode by jointly optimizing the
power allocation coefficients at the BS, the transmit power coefficient at the
relay user, and the passive beamforming at the RIS, subject to power budget
constraints, the successive interference cancellation constraint and the
minimum required quality-of-service at both cellular users. To address the
high-coupled optimization variables, an efficient algorithm is proposed by
invoking an alternating optimization approach that decomposes the original
problem into a power allocation sub-problem and a passive beamforming
sub-problem, which are solved alternately. For the power allocation
sub-problem, the optimal closed-form expressions for the power allocation
coefficients are derived. Meanwhile, the semi-definite relaxation approach is
exploited to tackle the passive beamforming sub-problem. The simulation results
validate the accuracy of the derived power control closed-form expressions and
demonstrate the gain in the total transmit power brought by integrating the RIS
in C-NOMA networks