Dynamic Resource Allocation for Transmit Power Minimization in OFDM-Based NOMA Systems

Li, Xunan; Li, Chong; Jin, Ye

doi:10.1109/lcomm.2016.2612688

Cited by 91 publications

(48 citation statements)

References 8 publications

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“…X´Y " σ 2 P k2,n,r`h 2 k1,n,r´h 2 k2,n,rZ´T "´σ 2 P k1,n,r`h 2 k1,n,r´h 2 k2,n,rT herefore, either (19) or (21) is positive, not both, which justifies why only the stronger user, the one with the higher channel gain, is able to perform SIC as it has been stated in all previous works on NOMA [8][9][10], [16], [17].…”

Section: A Theoretical Foundationmentioning

confidence: 61%

Power Minimization in Distributed Antenna Systems Using Non-Orthogonal Multiple Access and Mutual Successive Interference Cancellation

Farah

Kilzi

Nour

et al. 2018

IEEE Trans. Veh. Technol.

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This paper introduces new approaches for combining non-orthogonal multiple access with distributed antenna systems. The study targets a minimization of the total transmit power in each cell, under user rate and power multiplexing constraints. Several new suboptimal power allocation techniques are proposed. They are shown to yield very close performance to an optimal power allocation scheme. Also, a new approach based on mutual successive interference cancellation of paired users is proposed. Different techniques are designed for the joint allocation of subcarriers, antennas, and power, with a particular care given to maintain a moderate complexity. The coupling of non-orthogonal multiple access to distributed antenna systems is shown to greatly outperform any other combination of orthogonal/non-orthogonal multiple access schemes with distributed or centralized deployment scenarios.

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Section: A Theoretical Foundationmentioning

confidence: 61%

Power Minimization in Distributed Antenna Systems Using Non-Orthogonal Multiple Access and Mutual Successive Interference Cancellation

Farah

Kilzi

Nour

et al. 2018

IEEE Trans. Veh. Technol.

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“…In [29], [30], the joint power and channel allocation problem was resolved by decoupling it as a many-to-many matching game with externalities and a geometric programming subproblem. Apart from the maximization of the sum rate or weighted sum rate, the total transmit power minimization problems were addressed subject to the predefined QoS of individual users in [31], [32]. Very recently, Sun et al studied a full-duplex multi-carrier NOMA system, wherein the monotonic optimization was adopted to design an optimal joint power and subcarrier allocation policy such that the weighted sum system throughput is maximized.…”

Section: A Related Workmentioning

confidence: 99%

Joint Rate Control and Power Allocation for Non-Orthogonal Multiple Access Systems

Bao

Chen

et al. 2017

IEEE J. Select. Areas Commun.

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Abstract-This paper investigates the optimal resource allocation of a downlink non-orthogonal multiple access (NOMA) system consisting of one base station and multiple users. Unlike existing short-term NOMA designs that focused on the resource allocation for only the current transmission timeslot, we aim to maximize a long-term network utility by jointly optimizing the data rate control at the network layer and the power allocation among multiple users at the physical layer, subject to practical constraints on both the short-term and long-term power consumptions. To solve this problem, we leverage the recently-developed Lyapunov optimization framework to convert the original long-term optimization problem into a series of online rate control and power allocation problems in each timeslot. The power allocation problem, however, is shown to be non-convex in nature and thus cannot be solved with a standard method. However, we explore two structures of the optimal solution and develop a dynamic programming based power allocation algorithm, which can derive a globally optimal solution, with a polynomial computational complexity. Extensive simulation results are provided to evaluate the performance of the proposed joint rate control and power allocation framework for NOMA systems, which demonstrate that the proposed NOMA design can significantly outperform multiple benchmark schemes, including orthogonal multiple access (OMA) schemes with optimal power allocation and NOMA schemes with non-optimal power allocation, in terms of average throughput and data delay.

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“…Source nodes in different pairs transmit over orthogonal frequency bands, and therefore can be recovered independently. This approach is also known as OFDM-NOMA [9] but, for the sake of brevity, we shall simply refer it to as NOMA. We consider the worst case scenario, in which both source groups contain an equal (i.e., K) number of source nodes, such that relay nodes always receive superimposed signals.…”

Section: System Modelmentioning

confidence: 99%

Non-Orthogonal Multiple Access Combined With Random Linear Network Coded Cooperation

Khan¹,

Chatzigeorgiou²

2017

IEEE Signal Process. Lett.

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This letter considers two groups of source nodes. Each group transmits packets to its own designated destination node over single-hop links and via a cluster of relay nodes shared by both groups. In an effort to boost reliability without sacrificing throughput, a scheme is proposed, whereby packets at the relay nodes are combined using two methods; packets delivered by different groups are mixed using non-orthogonal multiple access principles, while packets originating from the same group are mixed using random linear network coding. An analytical framework that characterizes the performance of the proposed scheme is developed, compared to simulation results and benchmarked against a counterpart scheme that is based on orthogonal multiple access.Index Terms-Network coding, non-orthogonal multiple access, sparse random matrices, decoding probability, throughput. I. INTRODUCTIONRandom Linear Network Coding (RLNC) is a scheme that allows an intermediate node to combine and forward the data of multiple users in a single transmission, and can effectively improve network capacity [1]. RLNC has the inherent capability to achieve spatial diversity. For example, it has been shown in [2] that network coding can improve the diversity gain of networks that either contain distributed antenna systems or support cooperative relaying. Furthermore, RLNC can improve both the throughput [1] and the latency in a network [3] by reducing the number of distinct transmissions.The benefits of network coding have made it an attractive solution for challenges encountered in existing and future communication systems. For instance, it has been shown in [4] that by modifying the IEEE 802.11g frame structure, network coding combined with Orthogonal Frequency Division Multiplexing (OFDM) can significantly improve throughput. The importance of network-coded cooperation has been demonstrated in [5] and implemented in [6] with Orthogonal Frequency Multiple Access (OFDMA). Recently, Non-Orthogonal Multiple Access (NOMA) has been recognised as a promising multiple access technique for 5G mobile networks [7], [8]. It has been shown in [9], [10] that combining NOMA with OFDM can improve the spectral efficiency and accommodate more users than the conventional OFDMA-based systems. Moreover, the usefulness of RLNC for downlink NOMAbased transmissions has been studied in [11].This letter considers network-coded cooperation in a NOMA-based scenario with two groups of source nodes. Each

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Dynamic Resource Allocation for Transmit Power Minimization in OFDM-Based NOMA Systems

Cited by 91 publications

References 8 publications

Power Minimization in Distributed Antenna Systems Using Non-Orthogonal Multiple Access and Mutual Successive Interference Cancellation

Power Minimization in Distributed Antenna Systems Using Non-Orthogonal Multiple Access and Mutual Successive Interference Cancellation

Joint Rate Control and Power Allocation for Non-Orthogonal Multiple Access Systems

Non-Orthogonal Multiple Access Combined With Random Linear Network Coded Cooperation

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