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18 pages, 3413 KiB

Open AccessArticle

A Novel Machine Learning Scheme for mmWave Path Loss Modeling for 5G Communications in Dense Urban Scenarios

by Woobeen Jin, Hyeonjin Kim and Hyukjoon Lee

Electronics 2022, 11(12), 1809; https://doi.org/10.3390/electronics11121809 - 7 Jun 2022

Cited by 8 | Viewed by 2722

Accurate and efficient path loss prediction in mmWave communication plays an important role in large-scale deployment of the mmWave-based 5G mobile communication systems. Existing methods often present limitations in accuracy and efficiency and fail to fulfill the requirements of cell planning, especially in [...] Read more.

Accurate and efficient path loss prediction in mmWave communication plays an important role in large-scale deployment of the mmWave-based 5G mobile communication systems. Existing methods often present limitations in accuracy and efficiency and fail to fulfill the requirements of cell planning, especially in dense urban environments. In this paper, we propose a novel training method called multi-way local attentive learning, which allows for learning from multiple perspectives on the same set of training samples with local attention paid to each subset of the entire dataset. The sample data set can be partitioned in various ways with respect to different attributes, such that a larger amount of knowledge can be extracted from the same data set. The proposed scheme outperforms the existing schemes in terms of prediction accuracy at the average RMSE of 6.01 dBm. Full article

(This article belongs to the Special Issue Advanced Communication Techniques for 5G and Internet of Things)

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14 pages, 413 KiB

Open AccessArticle

Outage Constrained Design in NOMA-Based D2D Offloading Systems

by Yun Chen, Guoping Zhang, Hongbo Xu, Yinshuan Ren, Xue Chen and Ruijie Li

Electronics 2022, 11(2), 256; https://doi.org/10.3390/electronics11020256 - 13 Jan 2022

Cited by 8 | Viewed by 2288

Abstract

Non-orthogonal multiple access (NOMA) is a new multiple access method that has been considered in 5G cellular communications in recent years, and can provide better throughput than traditional orthogonal multiple access (OMA) to save communication bandwidth. Device-to-device (D2D) communication, as a key technology [...] Read more.

Non-orthogonal multiple access (NOMA) is a new multiple access method that has been considered in 5G cellular communications in recent years, and can provide better throughput than traditional orthogonal multiple access (OMA) to save communication bandwidth. Device-to-device (D2D) communication, as a key technology of 5G, can reuse network resources to improve the spectrum utilization of the entire communication network. Combining NOMA technology with D2D is an effective solution to improve mobile edge computing (MEC) communication throughput and user access density. Considering the estimation error of channel, we investigate the power of the transmit nodes optimization problem of NOMA-based D2D networks under the rates outage probability (OP) constraints of all single users. Specifically, under the channel statistical error model, the total system transmit power is minimized with the rate OP constraint of a single device. Unfortunately, the problem presented is thorny and non-convex. After equivalent transformation of the rate OP constraints by the Bernstein inequality, an algorithm based on semi-definite relaxation (SDR) can efficiently solve this challenging non-convex problem. Numerical results show that the channel estimation error increases the power consumption of the system. We also compare NOMA with the OMA mode, and the numerical results show that the D2D offloading systems based on NOMA are superior to OMA. Full article

(This article belongs to the Special Issue Advanced Communication Techniques for 5G and Internet of Things)

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23 pages, 787 KiB

Open AccessArticle

Optimization of the Spectrum Splitting and Auction for 5th Generation Mobile Networks to Enhance Quality of Services for IoT from the Perspective of Inclusive Sharing Economy

by Johannes K. Chiang, Chien-Liang Lin, Yi-Fang Chiang and Yushun Su

Electronics 2022, 11(1), 3; https://doi.org/10.3390/electronics11010003 - 21 Dec 2021

Cited by 9 | Viewed by 4240

Abstract

Fifth generation (5G) mobile networks can accomplish enhanced communication capabilities and desired to connect things in addition to people. By means of optimally splitting the spectrum to integrate more efficient segments, mobile operators can deliver better Quality of Services (QoS) for Internet of [...] Read more.

Fifth generation (5G) mobile networks can accomplish enhanced communication capabilities and desired to connect things in addition to people. By means of optimally splitting the spectrum to integrate more efficient segments, mobile operators can deliver better Quality of Services (QoS) for Internet of Things (IoT), even the nowadays so-called metaverse need broadband mobile communication. Drawing on the Theory of Quality Value Transformation, we developed a 5G ecosystem as a sustainable organic coalition constituted of planners, providers, and users. Most importantly, we put forward the altruism as the ethics drive for the organic cooperative evolution to sustain the inclusive sharing economy to solve the problem of the Theory of Games and Economic Behavior. On the top of the collaboration framework for the coalition game for 5G, we adopted Pareto Optimality as the target situation for the optimization via cooperative evolution and further apply ISO 25000 to define the metrics for the value of 5G corresponding to Pareto Frontier. Based on the collaboration framework as above, we conducted a survey to gather the features and costs for the 5G spectrum in relation to IoT and the financial status of the mobile operators as the constraint for the optimization. Taking Simultaneous Multi-Round Auction (SMRA) as the standard rule for spectrum auction, we developed a novel optimization program of two hybrid metaheuristics with the combination of Simulated Annealing (SA), Genetic Algorithm (GA), and Random Optimization (RO) for the multiple objectives of quality, usability, and costs. The results of the simulation show that the coalition game for 5G spectrum auction is a dynamic group decision in which the government authority and mobile operators can achieve a synergy to maximize the profits, quality score, and usability, and minimize the costs. Last but not least, the hybrid metaheuristic with SA and RO is more efficient and effective than that with GA and BO, from the perspective of inclusive sharing economy. It is the first study of its kind as we know. Full article

(This article belongs to the Special Issue Advanced Communication Techniques for 5G and Internet of Things)

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14 pages, 1104 KiB

Open AccessArticle

On the Symbol Error Probability of STBC-NOMA with Timing Offsets and Imperfect Successive Interference Cancellation

by Muhammad Waseem Akhtar, Syed Ali Hassan and Haejoon Jung

Electronics 2021, 10(12), 1386; https://doi.org/10.3390/electronics10121386 - 9 Jun 2021

Cited by 6 | Viewed by 2372

Abstract

Due to the ability to handle a large number of users, low latency, and high data rates, NON-orthogonal multiple access (NOMA) is considered a promising access technology for next-generation communication systems. However, as the number of users increases, each user experiences a greater [...] Read more.

Due to the ability to handle a large number of users, low latency, and high data rates, NON-orthogonal multiple access (NOMA) is considered a promising access technology for next-generation communication systems. However, as the number of users increases, each user experiences a greater number of successive interference cancellations (SIC), causing the system’s performance to decline. With the increase in the number of users, the fraction of power allocated to each user becomes smaller. Cooperative communication in downlink NOMA is considered as a potential approach to enhance the reliability, capacity, and performance over wireless channels. Space-time block code (STBC)-aided cooperative NOMA (CNOMA) offers an opportunity to improve the weak users’ signal-to-interference-plus-noise (SINR) through strong user cooperation. In this paper, we study the symbol error probability (SEP) performance of the STBC-NOMA and derive the asymptotic expression for SEP when the network is impaired with imperfect SIC (ipSIC) and timing offsets. The simulation results show that the performance of STBC-NOMA was degraded significantly with an increase in the imperfection of SIC and timing errors and that traditional orthogonal access schemes, such as orthogonal frequency division multiple access (OFDMA) and time division multiple access (TDMA), should be used after a threshold SIC level. Full article

(This article belongs to the Special Issue Advanced Communication Techniques for 5G and Internet of Things)

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14 pages, 988 KiB

Open AccessFeature PaperArticle

Zero-Keep Filter Pruning for Energy/Power Efficient Deep Neural Networks

by Yunhee Woo, Dongyoung Kim, Jaemin Jeong, Young-Woong Ko and Jeong-Gun Lee

Electronics 2021, 10(11), 1238; https://doi.org/10.3390/electronics10111238 - 22 May 2021

Cited by 5 | Viewed by 3156

Abstract

Recent deep learning models succeed in achieving high accuracy and fast inference time, but they require high-performance computing resources because they have a large number of parameters. However, not all systems have high-performance hardware. Sometimes, a deep learning model needs to be run [...] Read more.

Recent deep learning models succeed in achieving high accuracy and fast inference time, but they require high-performance computing resources because they have a large number of parameters. However, not all systems have high-performance hardware. Sometimes, a deep learning model needs to be run on edge devices such as IoT devices or smartphones. On edge devices, however, limited computing resources are available and the amount of computation must be reduced to launch the deep learning models. Pruning is one of the well-known approaches for deriving light-weight models by eliminating weights, channels or filters. In this work, we propose “zero-keep filter pruning” for energy-efficient deep neural networks. The proposed method maximizes the number of zero elements in filters by replacing small values with zero and pruning the filter that has the lowest number of zeros. In the conventional approach, the filters that have the highest number of zeros are generally pruned. As a result, through this zero-keep filter pruning, we can have the filters that have many zeros in a model. We compared the results of the proposed method with the random filter pruning and proved that our method shows better performance with many fewer non-zero elements with a marginal drop in accuracy. Finally, we discuss a possible multiplier architecture, zero-skip multiplier circuit, which skips the multiplications with zero to accelerate and reduce energy consumption. Full article

(This article belongs to the Special Issue Advanced Communication Techniques for 5G and Internet of Things)

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37 pages, 2954 KiB

Open AccessFeature PaperArticle

Multi-UAV Enabled Data Collection with Efficient Joint Adaptive Interference Management and Trajectory Design

by Weichao Pi and Jianming Zhou

Electronics 2021, 10(5), 547; https://doi.org/10.3390/electronics10050547 - 26 Feb 2021

Cited by 10 | Viewed by 2675

Abstract

This paper studies interference in a data collection scenario in which multiple unmanned aerial vehicles (UAVs) are dispatched to wirelessly collect data from a set of distributed sensors. To improve the communication throughput and minimize the completion time, we design a joint resource [...] Read more.

This paper studies interference in a data collection scenario in which multiple unmanned aerial vehicles (UAVs) are dispatched to wirelessly collect data from a set of distributed sensors. To improve the communication throughput and minimize the completion time, we design a joint resource allocation and trajectory optimization framework that not only is compatible with the traditional time-division scheme and interference coordination scheme but also combines their advantages. First, we analyse a basic quasi-stationary scenario with two UAVs and four devices, in which the two UAVs hover at optimal displacements to execute the data collection mission, and it is proven that the proposed optimal resource allocation and trajectory solution is adaptively adjustable according to the severity of the interference and that the common throughput of the network is non-decreasing. Second, for the general mobile case, we design an efficient algorithm to jointly address resource allocation and trajectory optimization, in which we first apply the block coordinate descent method to decompose the original non-convex problem into three non-convex sub-problems and then employ a dedicated genetic algorithm, a penalty function and the sequential convex approximation (SCA) technique to efficiently solve the individual sub-problems and obtain a satisfactory locally optimal solution with an adaptive initialization scheme. Subsequently, numerical experiments are presented to demonstrate that the completion time of the data collection task with our proposed method is at least 25% shorter than those with several baseline dynamic orthogonal schemes when 4 UAVs are deployed. Finally, we provide a practical application principle concerning the maximum suitable number of UAVs to avoid the inherent deficiencies of the proposed algorithm. Full article

(This article belongs to the Special Issue Advanced Communication Techniques for 5G and Internet of Things)

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26 pages, 2892 KiB

Open AccessEditor’s ChoiceArticle

A Survey of Candidate Waveforms for beyond 5G Systems

by Filipe Conceição, Marco Gomes, Vitor Silva, Rui Dinis, Adão Silva and Daniel Castanheira

Electronics 2021, 10(1), 21; https://doi.org/10.3390/electronics10010021 - 25 Dec 2020

Cited by 28 | Viewed by 4839

Abstract

The 5G and beyond future wireless networks aim to support a large variety of services with increasing demand in terms of data rate and throughput while providing a higher degree of reliability, keeping the overall system complexity affordable. One of the key aspects [...] Read more.

The 5G and beyond future wireless networks aim to support a large variety of services with increasing demand in terms of data rate and throughput while providing a higher degree of reliability, keeping the overall system complexity affordable. One of the key aspects regarding the physical layer architecture of such systems is the definition of the waveform to be used in the air interface. Such waveforms must be studied and compared in order to choose the most suitable and capable of providing the 5G and beyond services requirements, with flexible resource allocation in time and frequency domains, while providing high spectral and power efficiencies. In this paper, several beyond 5G waveforms candidates are presented, along with their transceiver architectures. Additionally, the associated advantages and disadvantages regarding the use of these transmission techniques are discussed. They are compared in a similar downlink transmission scenario where three main key performance indicators (KPIs) are evaluated. They are the peak-to-average power ratio, the overall system spectral efficiency (wherein the out of band emissions are measured, along with the spectral confinement of the power spectral density of the transmitted signals) and the bit error rate performance. Additionally, other KPIs are discussed. Full article

(This article belongs to the Special Issue Advanced Communication Techniques for 5G and Internet of Things)

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12 pages, 1027 KiB

Open AccessArticle

Neural Network Based AMP Method for Multi-User Detection in Massive Machine-Type Communication

by Mengjiang Sun and Peng Chen

Electronics 2020, 9(8), 1286; https://doi.org/10.3390/electronics9081286 - 11 Aug 2020

Viewed by 2714

Abstract

In massive machine-type communications (mMTC) scenarios, grant-free non-orthogonal multiple access becomes crucial due to the small transmission latency, limited signaling overhead and the ability to support massive connectivity. In a multi-user detection (MUD) problem, the base station (BS) is unaware of the active [...] Read more.

In massive machine-type communications (mMTC) scenarios, grant-free non-orthogonal multiple access becomes crucial due to the small transmission latency, limited signaling overhead and the ability to support massive connectivity. In a multi-user detection (MUD) problem, the base station (BS) is unaware of the active users and needs to detect active devices. With sporadic devices transmitting signals at any moment, the MUD problem can be formulated as a multiple measurement vector (MMV) sparse recovery problem. Through the Khatri–Rao product, we prove that the MMV problem is transformed into a single measurement vector (SMV) problem. Based on the basis pursuit de-noising approximate message passing (BPDN-AMP) algorithm, a novel learning AMP network (LAMPnet) algorithm is proposed, which is designed to reduce the false alarm probability when the required detection probability is high. Simulation results show that when the required detection probablity is high, the AMP algorithm based on LAMPnet noticeably outperforms the traditional algorithms with acceptable computational complexity. Full article

(This article belongs to the Special Issue Advanced Communication Techniques for 5G and Internet of Things)

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