NOMA-Enabled Cooperative Unicast–Multicast: Design and Outage Analysis

Yang, Long; Chen, Jian; Ni, Qiang; Shi, Jia; Xue, Xuan

doi:10.1109/twc.2017.2754261

Cited by 59 publications

(41 citation statements)

References 37 publications

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“…l∈A Ω g l,m . Combining (20) and (A.3) with the help of (A.2), a closed-form expression of Pr(O AU 2 ) is obtained as shown in (24). This completes the proof.…”

supporting

confidence: 52%

“…If the selected AU is successful after the first phase, it will forward both HP and LP messages during the second phase • Strategy-4: This strategy employs the best user selection (BUS) scheme for fixed power allocation [24], termed as F-BUS scheme, which selects the successful AU that maximizes the worst normalized reception quality of unsuccessful AUs and unsuccessful RUs, i.e.,…”

Section: B Performance Comparisonmentioning

confidence: 99%

“…When some users want the same data in NOMA systems, integrating wireless multicast into cooperative NOMA, i.e., cooperative NOMA multicast, is expected to combine their advantages. Motivated by this fact, two opportunistic cooperative NOMA multicast strategies are designed in most recent work [23] and [24], which opportunistically recruit a successful multicast user that helps forward its received messages to unsuccessful multicast/unicast users. It has been theoretically proved in [23] and [24] that, by appropriately selecting the successful multicast user, full diversity can be achieved at each multicast/unicast user.…”

Section: Introductionmentioning

confidence: 99%

“…However, the cooperative NOMA multicast strategies proposed in [23] and [24] have only focused on the non-layered multicast, which does not consider the heterogeneity among multicast users. In fact, as multicast users own heterogeneous and time-varying channel conditions, the non-layered multicast which employs fixed data-rate and coding scheme cannot best serve all multicast users simultaneously, especially in video multicast that requires seamless connectivity and low latency [25].…”

Section: Introductionmentioning

confidence: 99%

“…Further, by recruiting the users that successfully decode the multicast messages to serve as relays, great spatial diversity offered by cooperative NOMA can be harvested to improve the reliability/connectivity of layered multicast. Therefore, compared to the cooperative NOMA strategies for non-layered multicast in [23] and [24], the design of cooperative NOMA strategy for layered multicast is a more challenging and practically useful issue for video multicast in 5G systems. Specifically, in this novel design, the video information is encoded into data streams of highpriority (HP) and low-priority (LP), corresponding to the base-layer and enhancement-layer streams in the digital video broadcasting (DVB) [29].…”

Section: Introductionmentioning

confidence: 99%

See 4 more Smart Citations

Cooperative Non-Orthogonal Layered Multicast Multiple Access for Heterogeneous Networks

Yang

et al. 2019

IEEE Trans. Commun.

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This paper proposes a novel design of cooperative non-orthogonal layered multicast multiple access in a heterogeneous network, where the information is encoded into the messages of high-priority (HP) and low-priority (LP). Two types of multicast users coexist in the network: 1) regular users (RUs), which are located far away from the base-station (BS) and expect to decode only the HP message (due to the weak channels); 2) advanced users (AUs), which are located close to the BS and expect to decode both HP and LP messages. To improve the reliability of layered multicast, we consider that the successful AUs (those AUs who successfully decode the HP and LP messages) serve as potential relays to assist other AUs/RUs. Based on this idea, two novel cooperation strategies are proposed for different cases of channel information availability. For each proposed strategy, we derive closed-form exact outage probabilities of AUs and RUs, and then further analyze their diversity orders. Moreover, considering that the layered multicast is outage-constrained, we theoretically evaluate the energy consumption of both strategies and demonstrate their energy saving gains over the direct nonorthogonal multiple access for layered multicast. Finally, our theoretical analysis is verified by numerical results, and the advantages of the proposed strategies are also demonstrated.

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“…l∈A Ω g l,m . Combining (20) and (A.3) with the help of (A.2), a closed-form expression of Pr(O AU 2 ) is obtained as shown in (24). This completes the proof.…”

supporting

confidence: 52%

Section: B Performance Comparisonmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 3 more Smart Citations

Cooperative Non-Orthogonal Layered Multicast Multiple Access for Heterogeneous Networks

Yang

et al. 2019

IEEE Trans. Commun.

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Joint impacts of hardware impairments, imperfect CSIs, and interference constraints on underlay cooperative cognitive networks with reactive relay selection

Son

2018

Telecommun Syst

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In this paper, we investigate joint impacts of hardware impairments, imperfect channel state information (CSI) and interference constraints at secondary users in an underlay decode-and-forward cognitive network with multiple primary receivers, called as JIC protocol. A best secondary relay is derived from the reactive relay selection which maximizes signal-to-interferenceand-distortion-and-noise ratios from a candidates relay set to a secondary destination over Rayleigh fading channels. The exact and asymptotic closed-form outage probability expressions are obtained to evaluate the system performance of the JIC protocol, and then are verified by the Monte Carlo simulations. Contributions show performance degradation of the JIC protocol due to the hardware impairments, the imperfect CSIs, and the interference constraints, and the significant performance improvement with respect to optimal impairment levels and optimal relay locations as well as the increase in the number of the secondary relays. In addition, insightful discussions with the conventional direct transmission are provided. Finally, the exact and asymptotic closed-form expressions are valid to the simulation results.

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Power allocation and temporal fair user group scheduling for downlink NOMA

et al. 2021

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Non-Orthogonal Multiple Access (NOMA) has been proposed as a new radio access technique for cellular networks as an alternative to OMA (Orthogonal Multiple Access) in which the users of a group (pairs or triples of users in a group are considered in this paper) are allowed to use the wireless channel simultaneously. In this paper, for downlink single-input single-output SISO-NOMA, a heuristic power allocation algorithm within a group is first proposed which attempts to ensure that the users of a group benefit from simultaneous transmission equally in terms of achievable throughput. Moreover, a user group scheduling algorithm is proposed for downlink NOMA systems by which a user group is to be dynamically selected for transmission while satisfying long term temporal fairness among the individual contending users. The effectiveness of the proposed power allocation method along with the temporal fair scheduling algorithm for downlink NOMA is validated with simulations and the performance impact of the transmit power and the coverage radius of the base station as well as the number of users are thoroughly studied.

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NOMA-Enabled Cooperative Unicast–Multicast: Design and Outage Analysis

Cited by 59 publications

References 37 publications

Cooperative Non-Orthogonal Layered Multicast Multiple Access for Heterogeneous Networks

Cooperative Non-Orthogonal Layered Multicast Multiple Access for Heterogeneous Networks

Joint impacts of hardware impairments, imperfect CSIs, and interference constraints on underlay cooperative cognitive networks with reactive relay selection

Power allocation and temporal fair user group scheduling for downlink NOMA

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