182 research outputs found
Fairness Comparison of Uplink NOMA and OMA
In this paper, we compare the resource allocation fairness of uplink
communications between non-orthogonal multiple access (NOMA) schemes and
orthogonal multiple access (OMA) schemes. Through characterizing the
contribution of the individual user data rate to the system sum rate, we
analyze the fundamental reasons that NOMA offers a more fair resource
allocation than that of OMA in asymmetric channels. Furthermore, a fairness
indicator metric based on Jain's index is proposed to measure the asymmetry of
multiuser channels. More importantly, the proposed metric provides a selection
criterion for choosing between NOMA and OMA for fair resource allocation. Based
on this discussion, we propose a hybrid NOMA-OMA scheme to further enhance the
users fairness. Simulation results confirm the accuracy of the proposed metric
and demonstrate the fairness enhancement of the proposed hybrid NOMA-OMA scheme
compared to the conventional OMA and NOMA schemes.Comment: 6 pages, accepted for publication, VTC 2017, Spring, Sydne
A Survey of Downlink Non-orthogonal Multiple Access for 5G Wireless Communication Networks
Accepted by ZTE CommunicationsAccepted by ZTE CommunicationsAccepted by ZTE CommunicationsAccepted by ZTE CommunicationsAccepted by ZTE CommunicationsNon-orthogonal multiple access (NOMA) has been recognized as a promising multiple access technique for the next generation cellular communication networks. In this paper, we first discuss a simple NOMA model with two users served by a single-carrier simultaneously to illustrate its basic principles. Then, a more general model with multicarrier serving an arbitrary number of users on each subcarrier is also discussed. An overview of existing works on performance analysis, resource allocation, and multiple-input multiple-output NOMA are summarized and discussed. Furthermore, we discuss the key features of NOMA and its potential research challenges
Resource allocation for NOMA wireless systems
Power-domain non-orthogonal multiple access (NOMA) has been widely recognized as
a promising candidate for the next generation of wireless communication systems. By
applying superposition coding at the transmitter and successive interference cancellation
at the receiver, NOMA allows multiple users to access the same time-frequency resource
in power domain. This way, NOMA not only increases the system’s spectral and energy
efficiencies, but also supports more users when compared with the conventional orthogonal
multiple access (OMA). Meanwhile, improved user fairness can be achieved by NOMA.
Nonetheless, the promised advantages of NOMA cannot be realized without proper
resource allocation. The main resources in wireless communication systems include time,
frequency, space, code and power. In NOMA systems, multiple users are accommodated
in each time/frequency/code resource block (RB), forming a NOMA cluster. As a result,
how to group the users into NOMA clusters and allocate the power is of significance. A
large number of studies have been carried out for developing efficient power allocation
(PA) algorithms in single-input single-output (SISO) scenarios with fixed user clustering.
To fully reap the gain of NOMA, the design of joint PA and user clustering is required.
Moreover, the study of PA under multiple-input multiple-output (MIMO) systems still
remains at an incipient stage. In this dissertation, we develop novel algorithms to allocate
resource for both SISO-NOMA and MIMO-NOMA systems.
More specifically, Chapter 2 compares the system capacity of MIMO-NOMA with
MIMO-OMA. It is proved analytically that MIMO-NOMA outperforms MIMO-OMA in terms of both sum channel capacity and ergodic sum capacity when there are multiple
users in a cluster. Furthermore, it is demonstrated that the more users are admitted to
a cluster, the lower is the achieved sum rate, which illustrates the tradeoff between the
sum rate and maximum number of admitted users.
Chapter 3 addresses the PA problem for a general multi-cluster multi-user MIMONOMA
system to maximize the system energy efficiency (EE). First, a closed-form solution
is derived for the corresponding sum rate (SE) maximization problem. Then, the EE
maximization problem is solved by applying non-convex fractional programming.
Chapter 4 investigates the energy-efficient joint user-RB association and PA problem
for an uplink hybrid NOMA-OMA system. The considered problem requires to jointly
optimize the user clustering, channel assignment and power allocation. To address this
hard problem, a many-to-one bipartite graph is first constructed considering the users
and RBs as the two sets of nodes. Based on swap matching, a joint user-RB association
and power allocation scheme is proposed, which converges within a limited number of
iterations. Moreover, for the power allocation under a given user-RB association, a low complexity
optimal PA algorithm is proposed.
Furthermore, Chapter 5 focuses on securing the confidential information of massive
MIMO-NOMA networks by exploiting artificial noise (AN). An uplink training scheme is
first proposed, and on this basis, the base station precodes the confidential information
and injects the AN. Following this, the ergodic secrecy rate is derived for downlink transmission.
Additionally, PA algorithms are proposed to maximize the SE and EE of the
system.
Finally, conclusions are drawn and possible extensions to resource allocation in NOMA
systems are discussed in Chapter 6
Investigation on Evolving Single-Carrier NOMA into Multi-Carrier NOMA in 5G
© 2013 IEEE. Non-orthogonal multiple access (NOMA) is one promising technology, which provides high system capacity, low latency, and massive connectivity, to address several challenges in the fifth-generation wireless systems. In this paper, we first reveal that the NOMA techniques have evolved from single-carrier NOMA (SC-NOMA) into multi-carrier NOMA (MC-NOMA). Then, we comprehensively investigated on the basic principles, enabling schemes and evaluations of the two most promising MC-NOMA techniques, namely sparse code multiple access (SCMA) and pattern division multiple access (PDMA). Meanwhile, we consider that the research challenges of SCMA and PDMA might be addressed with the stimulation of the advanced and matured progress in SC-NOMA. Finally, yet importantly, we investigate the emerging applications, and point out the future research trends of the MC-NOMA techniques, which could be straightforwardly inspired by the various deployments of SC-NOMA
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