263 research outputs found
Performance Analysis of SSK-NOMA
In this paper, we consider the combination between two promising techniques:
space-shift keying (SSK) and non-orthogonal multiple access (NOMA) for future
radio access networks. We analyze the performance of SSK-NOMA networks and
provide a comprehensive analytical framework of SSK-NOMA regarding bit error
probability (BEP), ergodic capacity and outage probability. It is worth
pointing out all analysis also stand for conventional SIMO-NOMA networks. We
derive closed-form exact average BEP (ABEP) expressions when the number of
users in a resource block is equal to i.e., . Nevertheless, we analyze the
ABEP of users when the number of users is more than i.e., , and derive
bit-error-rate (BER) union bound since the error propagation due to iterative
successive interference canceler (SIC) makes the exact analysis intractable.
Then, we analyze the achievable rate of users and derive exact ergodic capacity
of the users so the ergodic sum rate of the system in closed-forms. Moreover,
we provide the average outage probability of the users exactly in the
closed-form. All derived expressions are validated via Monte Carlo simulations
and it is proved that SSK-NOMA outperforms conventional NOMA networks in terms
of all performance metrics (i.e., BER, sum rate, outage). Finally, the effect
of the power allocation (PA) on the performance of SSK-NOMA networks is
investigated and the optimum PA is discussed under BER and outage constraints
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
D3.2 First performance results for multi -node/multi -antenna transmission technologies
This deliverable describes the current results of the multi-node/multi-antenna technologies
investigated within METIS and analyses the interactions within and outside Work Package 3.
Furthermore, it identifies the most promising technologies based on the current state of
obtained results. This document provides a brief overview of the results in its first part. The second part, namely the Appendix, further details the results, describes the simulation
alignment efforts conducted in the Work Package and the interaction of the Test Cases. The
results described here show that the investigations conducted in Work Package 3
are maturing resulting in valuable innovative solutions for future 5G systems.Fantini. R.; Santos, A.; De Carvalho, E.; Rajatheva, N.; Popovski, P.; Baracca, P.; Aziz, D.... (2014). D3.2 First performance results for multi -node/multi -antenna transmission technologies. http://hdl.handle.net/10251/7675
5G Downlink Throughput Enhancement by Beams Consolidating at Vacant Traffic
The 3GPP release for 5G (R15) assigns each User Equipment (UE) a radio beam by employing Massive Multi-User MU-Multiple-Input-Multiple-Output (MIMO) technology. Each beam carries, at the downlink, a data rate according to the modulation and coding scheme (MCS) assigned by the base station (BS). For the limited existence of active UEs and during vacant traffic or standby UEs, the assigned beams will be transmitted, but not to any UE. This paper proposes a new scheme that consolidates vacant beams of inactive UEs, to the adjacent beam of the active UE or UE at the cell edge to duplicate the bandwidth of the new beam. The proposed scheme increases the level of desired modulation and coding scheme (MCS) to a higher scheme and hence enhances the spectral efficiency (SE) of the 5G mobile networks. Specifically, the BS consolidates (combines) multiple radio beams along with the assigned beam during vacant traffic. More than two beams are consolidated in particular to the active UE to increase the bit rate by assigning higher MCS. The simulation evaluation depicted that the performance of beams consolidation provides a gain of 3.5 dB above than the state before beams consolidation. Moreover, more than 40 % improvement in UE throughput is achieved
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
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