299 research outputs found
Energy-Efficient NOMA Enabled Heterogeneous Cloud Radio Access Networks
Heterogeneous cloud radio access networks (H-CRANs) are envisioned to be
promising in the fifth generation (5G) wireless networks. H-CRANs enable users
to enjoy diverse services with high energy efficiency, high spectral
efficiency, and low-cost operation, which are achieved by using cloud computing
and virtualization techniques. However, H-CRANs face many technical challenges
due to massive user connectivity, increasingly severe spectrum scarcity and
energy-constrained devices. These challenges may significantly decrease the
quality of service of users if not properly tackled. Non-orthogonal multiple
access (NOMA) schemes exploit non-orthogonal resources to provide services for
multiple users and are receiving increasing attention for their potential of
improving spectral and energy efficiency in 5G networks. In this article a
framework for energy-efficient NOMA H-CRANs is presented. The enabling
technologies for NOMA H-CRANs are surveyed. Challenges to implement these
technologies and open issues are discussed. This article also presents the
performance evaluation on energy efficiency of H-CRANs with NOMA.Comment: This work has been accepted by IEEE Network. Pages 18, Figure
Resource Allocation in the RIS Assisted SCMA Cellular Network Coexisting with D2D Communications
The cellular network coexisting with device-to-device (D2D) communications
has been studied extensively. Reconfigurable intelligent surface (RIS) and
non-orthogonal multiple access (NOMA) are promising technologies for the
evolution of 5G, 6G and beyond. Besides, sparse code multiple access (SCMA) is
considered suitable for next-generation wireless network in code-domain NOMA.
In this paper, we consider the RIS-aided uplink SCMA cellular network
simultaneously with D2D users. We formulate the optimization problem which aims
to maximize the cellular sum-rate by jointly designing D2D users resource block
(RB) association, the transmitted power for both cellular users and D2D users,
and the phase shifts at the RIS. The power limitation and users communication
requirements are considered. The problem is non-convex, and it is challenging
to solve it directly. To handle this optimization problem, we propose an
efficient iterative algorithm based on block coordinate descent (BCD) method.
The original problem is decoupled into three subproblems to solve separately.
Simulation results demonstrate that the proposed scheme can significantly
improve the sum-rate performance over various schemes.Comment: IEEE Acces
Energy-efficient non-orthogonal multiple access for wireless communication system
Non-orthogonal multiple access (NOMA) has been recognized as a potential solution for enhancing the throughput of next-generation wireless communications. NOMA is a potential option for 5G networks due to its superiority in providing better spectrum efficiency (SE) compared to orthogonal multiple access (OMA). From the perspective of green communication, energy efficiency (EE) has become a new performance indicator. A systematic literature review is conducted to investigate the available energy efficient approach researchers have employed in NOMA. We identified 19 subcategories related to EE in NOMA out of 108 publications where 92 publications are from the IEEE website. To help the reader comprehend, a summary for each category is explained and elaborated in detail. From the literature review, it had been observed that NOMA can enhance the EE of wireless communication systems. At the end of this survey, future research particularly in machine learning algorithms such as reinforcement learning (RL) and deep reinforcement learning (DRL) for NOMA are also discussed
Effective relaying mechanisms in future device to device communication : a thesis presented in partial fulfilment of the requirements for the degree of Doctor of Philosophy in School of Food and Advanced Technology at Massey University, Palmerston North, New Zealand
Listed in 2020 Dean's List of Exceptional ThesesFuture wireless networks embrace a large number of assorted network-enabled devices
such as mobile phones, sensor nodes, drones, smart gears, etc., with different applications
and purpose, but they all share one common characteristic which is the dependence
on strong network connectivity. Growing demand of internet-connected devices
and data applications is burdensome for the currently deployed cellular wireless networks.
For this reason, future networks are likely to embrace cutting-edge technological
advancements in network infrastructure such as, small cells, device-to-device communication,
non-orthogonal multiple access scheme (NOMA), multiple-input-multiple out,
etc., to increase spectral efficiency, improve network coverage, and reduce network latency.
Individual devices acquire network connectivity by accessing radio resources in
orthogonal manner which limits spectrum utilisation resulting in data congestion and
latency in dense cellular networks. NOMA is a prominent scheme in which multiple
users are paired together and access radio resources by slicing the power domain. While
several research works study power control mechanisms by base station to communicate
with NOMA users, it is equally important to maintain distinction between the
users in uplink communication. Furthermore, these users in a NOMA pair are able to
perform cooperative relaying where one device assists another device in a NOMA pair
to increase signal diversity. However, the benefits of using a NOMA pair in improving
network coverage is still overlooked. With a varierty of cellular connected devices, use
of NOMA is studied on devices with similar channel characteristics and the need of
adopting NOMA for aerial devices has not been investigated. Therefore, this research
establishes a novel mechanism to offer distinction in uplink communication for NOMA
pair, a relaying scheme to extend the coverage of a base station by utilising NOMA
pair and a ranking scheme for ground and aerial devices to access radio resources by
NOMA
Energy-Efficiency Maximization for a WPT-D2D Pair in a MISO-NOMA Downlink Network
The combination of non-orthogonal multiple access (NOMA) and wireless power
transfer (WPT) is a promising solution to enhance the energy efficiency of
Device-to-Device (D2D) enabled wireless communication networks. In this paper,
we focus on maximizing the energy efficiency of a WPT-D2D pair in a
multiple-input single-output (MISO)-NOMA downlink network, by alternatively
optimizing the beamforming vectors of the base station (BS) and the time
switching coefficient of the WPT assisted D2D transmitter. The formulated
energy efficiency maximization problem is non-convex due to the highly coupled
variables. To efficiently address the non-convex problem, we first divide it
into two subproblems. Afterwards, an alternating algorithm based on the
Dinkelbach method and quadratic transform is proposed to solve the two
subproblems iteratively. To verify the proposed alternating algorithm's
accuracy, partial exhaustive search algorithm is proposed as a benchmark. We
also utilize a deep reinforcement learning (DRL) method to solve the non-convex
problem and compare it with the proposed algorithm. To demonstrate the
respective superiority of the proposed algorithm and DRL-based method,
simulations are performed for two scenarios of perfect and imperfect channel
state information (CSI). Simulation results are provided to compare NOMA and
orthogonal multiple access (OMA), which demonstrate the superior performance of
energy efficiency of the NOMA scheme
Energy Efficiency Optimization for D2D Communications Underlaying UAV-assisted Industrial IoT Networks with SWIPT
The industrial Internet of Things (IIoT) has been viewed as a typical application for the fifth generation (5G) mobile networks. This paper investigates the energy efficiency (EE) optimization problem for the device-to-device (D2D) communications underlaying unmanned aerial vehicles (UAVs)-assisted IIoT networks with simultaneous wireless information and power transfer (SWIPT). We aim to maximize the EE of the system while satisfying the constraints of transmission rate and transmission power budget. However, the designed EE optimization problem is non-convex involving joint optimization of the UAV’s location, beam pattern, power control and time scheduling, which is difficult to tackle directly. To solve this problem, we present a joint UAV location and resource allocation algorithm to decouple the original problem into several sub-problems and solve them sequentially. Specifically, we first apply the Dinkelbach method to transform the fraction problem to a subtractive-form one, and propose a mulitiobjective evolutionary algorithm based on decomposition (MOEA/D) based algorithm to optimize the beam pattern. We then optimize UAV’s location and power control using the successive convex optimization techniques. Finally, after solving the above variables, the original problem can be transformed into a single-variable problem with respect to the charging time, which is linear and can be tackled directly. Numerical results verify that significant EE gain can be obtained by our proposed algorithm as compared to the benchmark schemes
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