Throughput Performance of Relay Backhaul Enhancement Using 3D Beamforming

Utatsu, Hiroki; Osawa, Kai; Mashino, Jun; Suyama, Satoshi; Otsuka, Hiroyuki

doi:10.1109/icoin.2019.8718197

Cited by 4 publications

(6 citation statements)

References 13 publications

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“…where x r i is the received signal at the i-th antenna of the relay node, P s i is the transmission power of the source node S i , h ij,1 is the Rayleigh channel coefficient of the link between the source node S j and the i-th antenna of the relay node in the MA stage with zero mean and variance δ 2 ij , n i,1 is the AWGN at the i-th antenna of the relay node with zero mean and variance σ 2 i , and x i is the signal sent by the source node S i , which is modulated with the binary phase-shift keying modulation.…”

Section: Ssmf-based Pnc Schemementioning

confidence: 99%

“…In most studies of the DF scheme, the relay node mapped the superposition signals into GF(2) by specific mapping rules. Here, GF (2) represented the binary Galois Field (GF). Different from those, in the SMF scheme, after the relay node received the superposition signals, it firstly used the zero forcing (ZF) algorithm to correct the distortion introduced by the channel.…”

Section: Introductionmentioning

confidence: 99%

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Optimized Antenna Selection and Adaptive Power Allocation for Physical Layer Network Coding with Selective Soft-Message-Forward Cooperation

et al. 2020

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To improve the systematic bit error rate (BER) performance and power efficiency, an optimized antenna selection and adaptive power allocation scheme is proposed for physical layer network coding (PNC) with selective soft-message-forward (SSMF) cooperation. In this scheme, two adaptive power allocation (APA) schemes are proposed for the multiple access (MA) and broadcast (BC) stages, respectively. In the MA stage, the APA scheme aims to maximize the Euclidean distance of network coding symbols received by relay node. In the second BC stage, the relay node takes the maximization of the minimum mutual information of two source nodes as objective function. Then it uses the narrow range method (NRM) to select the optimal antenna set and equally allocates power to them. To further reduce the systematic complexity, an antenna set pre-selection is proposed. It minimizes the antenna number in the initial antenna set of the NRM based on the deletion standard which does not reduce the mutual information in the BC stage. Simulation results indicate that our APA schemes surpass the existing equal power allocation (EPA) scheme with a binary phase-shift keying modulation. Compared with current EPA scheme, the proposed APA schemes for the BC, MA and global stages obtain about 1 dB, 2 dB and 3.5 dB performance gains at BER of 10 −3 with two antennas in the relay node, respectively. INDEX TERMS Physical layer network coding, selective soft-message-forward, antenna selection, adaptive power allocation.

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Section: Ssmf-based Pnc Schemementioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Optimized Antenna Selection and Adaptive Power Allocation for Physical Layer Network Coding with Selective Soft-Message-Forward Cooperation

et al. 2020

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“…Two dimensional precoding paradigm is applied for 3D massive antennas systems in [25]. In [20], the user experience 2 throughput in relay systems with exploiting 3DBF is evaluated. The authors in [4], study BF in NOMA-based MISO networks with considering two performance metrics, namely, sum data rate and fairness.…”

Section: B Related Workmentioning

confidence: 99%

“…To this end, firstly, we introduce new variables, then merge the integer variable with continues variable, and exploit the SCA technique. By these transformations, the well-known traditional sub-optimal solution, i.e., ASM, that is widely applied for solving non-convex and NP-hard problems is not required to solve problem (20). The main two steps of JS-CIV are in the following.…”

Section: Solution Of Optimization Problemmentioning

confidence: 99%

“…Furthermore, the beam pattern in physical layer has significant impacts on the performance of wireless network; especially for the high losses of propagation at high frequency bands [6]. Three-dimensional beam-forming (3DBF) combining the horizontal and vertical pattern allocation with large number of antennas is one of the most promising technologies for 5G [6], [17]- [20]. As studied in [21], interference management is a key limiting factor in increasing the capacity of heterogeneous networks (HetNets).…”

Section: Introduction a State Of The Artmentioning

confidence: 99%

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Joint Radio Resource Allocation and 3D Beam-forming in MISO-NOMA-based Network with Profit Maximization for Mobile Virtual Network Operators

Zakeri,

Mokari,

Yanikomeroglu

2019

Preprint

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Massive connections and high data rate services are key players in 5G ecosystem and beyond. To satisfy the requirements of these types of services, non orthogonal multiple Access (NOMA) and 3-dimensional beam-forming (3DBF) can be exploited. In this paper, we devise a novel radio resource allocation and 3D multiple input single output (MISO) BF algorithm in NOMA-based heterogeneous networks (HetNets) at which our main aim is to maximize the profit of mobile virtual network operators (MVNOs). To this end, we consider multiple infrastructure providers (InPs) and MVNOs serving multiple users. Each InP has multiple access points as base stations (BSs) with specified spectrum and multi-beam antenna array in each transmitter that share its spectrum with MVNO's users by employing NOMA. To realize this, we formulate a novel optimization problem at which the main aim is to maximize the revenue of MVNOs, subject to resource limitations and quality of service (QoS) constraints. Since our proposed optimization problem is non-convex and mathematically intractable, we transform it into a convex one by introducing a new optimization variable and converting the variables with adopting successive convex approximation. More importantly, the proposed solution is assessed and compared with the alternative search method and the optimal solution that is obtained with adopting the exhaustive search method. In addition, it is studied from the computational complexity, convergence, and performance perspective. Our simulation results demonstrate that NOMA-3DBF has better performance and increases system throughput and MVNO's revenue compared to orthogonal multiple access with 2DBF by approximately 64%. Especially, by exploiting 3DBF the MVNO's revenue is improved nearly 27% in contrast to 2DBF in high order of antennas.

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Precoder Design for Communication-Efficient Distributed MIMO Receivers With Controlled Peak-Average Power Ratio

Vaishampayan

2021

IEEE Trans. Commun.

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Throughput Performance of Relay Backhaul Enhancement Using 3D Beamforming

Cited by 4 publications

References 13 publications

Optimized Antenna Selection and Adaptive Power Allocation for Physical Layer Network Coding with Selective Soft-Message-Forward Cooperation

Optimized Antenna Selection and Adaptive Power Allocation for Physical Layer Network Coding with Selective Soft-Message-Forward Cooperation

Joint Radio Resource Allocation and 3D Beam-forming in MISO-NOMA-based Network with Profit Maximization for Mobile Virtual Network Operators

Precoder Design for Communication-Efficient Distributed MIMO Receivers With Controlled Peak-Average Power Ratio

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