Next Generation 5G Wireless Networks: A Comprehensive Survey

Agiwal, Mamta; Roy, Abhishek; Saxena, Navrati

doi:10.1109/comst.2016.2532458

Cited by 2,828 publications

(1,558 citation statements)

References 181 publications

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“…Based on the structure of R NOMA ks,n , we can apply AGMA approximation to propose the monomial approximation of R NOMA ks,n . At iteration t 1 , R NOMA ks,n can be Algorithm 1 : Iterative Algorithm Based on CGP for NOMA Initialization: Set t 1 = 1, β(t 1 ) = [1], where 1 is a vector C 1×K .…”

Section: A Iterative Algorithm For Noma-based Resource Allocationmentioning

confidence: 99%

“…Algorithm 2 : OFDMA Initialization: Set t 2 = 1, α(t 2 ) = [1], where 1 is a vector C 1×KN , p ks,n (t 2 ) = 1, ∀k s ∈ K s , ∀s ∈ S, ∀n ∈ N , t max 2 = 5000.…”

Section: A Proof Of Propositionmentioning

confidence: 99%

“…Moreover, the wireless service providers face a challenge in reducing the operational costs of the wireless infrastructure. As such, various techniques such as massive MIMO, virtualization, non-orthogonal multiple access have been envisioned for the next generation of wireless network in order to address these challenge [1]. Virtualization of wireless networks is a promising technique, in which the physical wireless infrastructure is shared among multiple service providers (SPs), also called slices [2].…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Power-Efficient Resource Allocation in NOMA Virtualized Wireless Networks

Dawadi

Parsaeefard

Derakhshani

et al. 2016

2016 IEEE Global Communications Conference (GLOBECOM)

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Section: A Iterative Algorithm For Noma-based Resource Allocationmentioning

confidence: 99%

“…Algorithm 2 : OFDMA Initialization: Set t 2 = 1, α(t 2 ) = [1], where 1 is a vector C 1×KN , p ks,n (t 2 ) = 1, ∀k s ∈ K s , ∀s ∈ S, ∀n ∈ N , t max 2 = 5000.…”

Section: A Proof Of Propositionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Power-Efficient Resource Allocation in NOMA Virtualized Wireless Networks

Dawadi

Parsaeefard

Derakhshani

et al. 2016

2016 IEEE Global Communications Conference (GLOBECOM)

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“…Consequently, in the development of next-generation wireless systems, it is a crucial task to provide wireless connections with better QoS such as higher data rate, smaller delay etc. [1], [2]. However, such task is not easy due to many inherent challenges.…”

Section: Introduction 11 Motivationmentioning

confidence: 99%

Radio Resource Allocation Over Fading Channels Under Statistical Delay Constraints

Phan¹,

Le‐Ngoc²

2017

SpringerBriefs in Electrical and Computer Engineering

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Wireless data transmission suffers from the fading nature of wireless channels, where the instantaneous channel conditions and hence transmission rates randomly fluctuate over time. Consequently, data arrivals at each transmitter might not be transmitted instantly. To cope with this situation, the transmitter employs buffer to store the data temporarily for later transmission. While data buffering enables more efficient radio resource allocation to opportunistically select the favorable fading conditions for transmission, it introduces queuing delay that needs to be controlled in order to meet the end-to-end delay quality-ofservice (QoS) requirements in supporting delay-sensitive communications. In this thesis, we study and develop radio resource allocation schemes for buffer-aided communications over wireless fading channels under statistical delay constraints. Using the buffering capability as a means to exploit the fading diversity, the nodes (source and relay) perform resource allocation, and adapt their transmissions to the channel state information (CSI) in order to enhance the system throughput while maintaining the statistical delay QoS requirements in terms of upper-bounded average delay or delay-outage probability.The thesis starts by considering a source-destination communications link over a fading channel with data arriving at the source transmission buffer. In the first scenario, the source is assumed to have a maximum power constraint and an average delay constraint. We consider admission control applied on random data arrivals to the source buffer in order to avoid constraint violation, and study the joint optimal data admission control and power allocation (AC-PA) problem for throughput maximization. In the second scenario, we consider an energy-harvesting (EH) source, where random amounts of energy are harvested from renewable energy sources, and stored in a battery during the course of data transmission. In every transmission time slot, the source is constrained to use at most the amount of energy currently stored. We then explore optimal power allocation problems for such EH systems under average delay or delay-outage constraints. We formulate the problems as infinite horizon constrained Markov decision process (MDP) problems, which incorporate the random variations of the fading channel, data arrival, and EH processes. A novel solution approach based on post-decision state-value function is proposed to study the properties of the optimal solutions. We also propose online allocation algorithms when the statistical knowledge of the random processes is unknown, which is typical in real-life communications. Illustrative results demonstrate the effectiveness of the proposed algorithms over existing approaches iii under similar power and delay constraints.The thesis continues with a source-relay-destination communications link over fading channels with buffers available at both source and relay, as part of a multi-hop network. We investigate and develop optimal resource allocation schemes ...

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“…In addition to the explained new issues, wireless access technology itself should also be enhanced in 5G [18]. The first one is massive multiple-input multiple-output (MIMO) technologies [19]- [21] for further enhancement of spatial spectral efficiency, as well as for its application to beamforming/beamtracking to achieve higher user rate.…”

Section: Introductionmentioning

confidence: 99%

Development of Wireless Access and Flexible Networking Technologies for 5G Cellular Systems

Sampei

2017

IEICE Trans. Commun.

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Next Generation 5G Wireless Networks: A Comprehensive Survey

Cited by 2,828 publications

References 181 publications

Power-Efficient Resource Allocation in NOMA Virtualized Wireless Networks

Power-Efficient Resource Allocation in NOMA Virtualized Wireless Networks

Radio Resource Allocation Over Fading Channels Under Statistical Delay Constraints

Development of Wireless Access and Flexible Networking Technologies for 5G Cellular Systems

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