Performance of transmit antenna selection in non-orthogonal multiple access for 5G systems

Shrestha, Anish Prasad; Bai, Zhiquan; Kim, Jae Myoung; Kwak, Kyung Sup

doi:10.1109/icufn.2016.7536954

Cited by 31 publications

(32 citation statements)

References 14 publications

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“…The authors of [17] and [18] investigated the performance of an energy harvesting AF relaying NOMA system with TAS scheme and closedform expressions for OP was obtained. A new TAS scheme for multiple-input single-output (MISO) NOMA systems was proposed in [19] and their result testified that higher performance can be obtained with multiple antennas at base station. The authors in [20] proposed an antenna selection algorithm to achieve near-optimal performance and reduce complexity.…”

Section: A Background and Related Workmentioning

confidence: 99%

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Secrecy Outage of Max–Min TAS Scheme in MIMO-NOMA Systems

Lei

Zhang

Park

et al. 2018

IEEE Trans. Veh. Technol.

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Section: A Background and Related Workmentioning

confidence: 99%

“…Obviously, P g,Y out,i is obtained based on (15), (19), and (20). Then the SOP of the MIMO-NOMA system with MM TAS is achieved by substituting (18) and (15) into (11).…”

Section: B Eavesdroppers With Collusionmentioning

confidence: 99%

Secrecy Outage of Max–Min TAS Scheme in MIMO-NOMA Systems

Lei

Zhang

Park

et al. 2018

IEEE Trans. Veh. Technol.

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“…Moreover, an efficient search algorithm provides a better trade-off between system performance and complexity, rather than a joint antenna and user contribution algorithm. Unfortunately, neither the authors of [41] nor the authors of [42] have studied the system performance analytically.…”

Section: Mimo-nomamentioning

confidence: 99%

A Tutorial on Nonorthogonal Multiple Access for 5G and Beyond

Aldababsa

Toka

Gökçeli

et al. 2018

Wireless Communications and Mobile Computing

233

168

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Today's wireless networks allocate radio resources to users based on the orthogonal multiple access (OMA) principle. However, as the number of users increases, OMA based approaches may not meet the stringent emerging requirements including very high spectral efficiency, very low latency, and massive device connectivity. Nonorthogonal multiple access (NOMA) principle emerges as a solution to improve the spectral efficiency while allowing some degree of multiple access interference at receivers. In this tutorial style paper, we target providing a unified model for NOMA, including uplink and downlink transmissions, along with the extensions to multiple input multiple output and cooperative communication scenarios. Through numerical examples, we compare the performances of OMA and NOMA networks. Implementation aspects and open issues are also detailed.

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“…There are only a few papers that considered the AS problem for MIMO-NOMA systems in the open literature. Specifically, a transmit AS (TAS) algorithm was proposed in [21], and a joint TAS and user scheduling algorithm was considered in [22]. However, both [21] and [22] only focused on the TAS design at the base station (BS) side and there were no analytical characterization of the system performance for the proposed algorithms.…”

Section: Introductionmentioning

confidence: 99%

Antenna Selection for MIMO Nonorthogonal Multiple Access Systems

Chen

et al. 2018

IEEE Trans. Veh. Technol.

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Abstract-This paper considers the antenna selection (AS) problem for a MIMO non-orthogonal multiple access (NOMA) system. In particular, we develop new computationally-efficient AS algorithms for two commonly-used scenarios: NOMA with fixed power allocation (F-NOMA) and NOMA with cognitive radio-inspired power allocation (CR-NOMA), respectively. For the F-NOMA scenario, a new max-max-max antenna selection (A 3 -AS) scheme is firstly proposed to maximize the system sumrate. This is achieved by selecting one antenna at the base station (BS) and corresponding best receive antenna at each user that maximizes the channel gain of the resulting strong user. To improve the user fairness, a new max-min-max antenna selection (AIA-AS) scheme is subsequently developed, in which we jointly select one transmit antenna at BS and corresponding best receive antennas at users to maximize the channel gain of the resulting weak user. For the CR-NOMA scenario, we propose another new antenna selection algorithm, termed maximumchannel-gain-based antenna selection (MCG-AS), to maximize the achievable rate of the secondary user, under the condition that the primary user's quality-of-service requirement is satisfied. The asymptotic closed-form expressions of the average sumrate for A 3 -AS and AIA-AS and that of the average rate of the secondary user for MCG-AS are derived, respectively. Numerical results demonstrate that the AIA-AS provides better user-fairness, while the A 3 -AS achieves a near-optimal sum-rate in F-NOMA systems. For the CR-NOMA scenario, MCG-AS achieves a near-optimal performance in a wide signal-to-noiseratio regime. Furthermore, all the proposed AS algorithms yield a significant computational complexity reduction, compared to exhaustive search-based counterparts.Index Terms-Multiple-input multiple-output (MIMO), nonorthogonal multiple access (NOMA), antenna selection (AS).

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Performance of transmit antenna selection in non-orthogonal multiple access for 5G systems

Cited by 31 publications

References 14 publications

Secrecy Outage of Max–Min TAS Scheme in MIMO-NOMA Systems

Secrecy Outage of Max–Min TAS Scheme in MIMO-NOMA Systems

A Tutorial on Nonorthogonal Multiple Access for 5G and Beyond

Antenna Selection for MIMO Nonorthogonal Multiple Access Systems

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