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Millimeter Wave Wireless Communications and Networks

A special issue of Sensors (ISSN 1424-8220). This special issue belongs to the section "Sensor Networks".

Deadline for manuscript submissions: closed (31 May 2016) | Viewed by 92088

Special Issue Editors


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Guest Editor
School of Electrical and Information Engineering, The University of Sydney, Sydney, NSW 2006, Australia
Interests: millimeter-wave wireless communications; machine-to-machine communications; cooperative communications; coding techniques; wireless sensor networks
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Guest Editor
1 Dept. Wireless Communications and Networks Fraunhofer Heirich-Hertz-Institute, Germany
2 Dept. Electrical and Electronic Engineering Tokyo Institute of Technology, Japan
Interests: 5G; millimeter-wave; heterogeneous networks; MIMO; wireless energy transfer
Department of Electronic Engineering, Tsinghua University, Rohm Building 10-202, Beijing 100084, China
Interests: urban sensing and computing; wireless sensor networks; mobile big data; mobile computing; social networks; network science and future internet

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Guest Editor
School of Electrical and Information Engineering, The University of Sydney, Sydney, NSW 2006, Australia
Interests: millimeter-wave wireless communications; wireless energy transfer and harvesting; cooperative communications; smart gird; game theory and distributed optimziation theory

Special Issue Information

Dear Colleagues,

Global mobile data traffic is doubling every year, and this trend will continue through the next decade. It is predicted that, within the next ten years, trillions of devices will connect to mobile networks. They will generate a more than 1000-time increase in mobile traffic and result in a spectrum shortage and clogged networks. This spectrum shortage will propel an increase in dropped calls, a rise in mobile data prices, and slowing of data speeds, a nightmare scenario for wireless operators and consumers.

This global spectrum crisis has motivated the exploration of underutilized millimeter wave (mmWave) frequency spectrum from 30 G–300 GHz for future mobile broadband communication networks. Large expanses of a new spectrum in this band could be opened up. Currently, the mmWave unlicensed band at 60 GHz is exploited in the next generation of wireless local area networks to support multi-gigabit data transmissions. Furthermore, mmWave licensed spectrum at other frequencies has been demonstrated to be feasible for 5G cellular systems.

In this Special Issue, we solicit original papers with high quality related to millimeter wave communications and networks. Contributions may include, but are not limited to:

  • Propagation measurements and channel modeling in mmWave bands
  • Efficient mmWave channel estimation algorithms
  • Massive MIMO for mmWave communications (e.g., transceiver desgin)
  • Wireless back/front haul using mmWave communictions
  • 5G cellular networks utilizing mmWave spectrum
  • Cooperative and relay techniques for mmWave communictions
  • Coding techniques for mmWave systems
  • Wireless energy transfer and harvesting in mmWave bands
  • New MAC and routing protocols for mmWave communication networks
  • Novel mobile network architectures supporting mmWave systems
  • C/U plane seperation in 5G networks involving mmWaves
  • mmWave communication systems prototyping
  • New applications of mmWave techniques to other networks

Dr. Yonghui Li
Dr. Kei Sakaguchi
Dr. Yong Li
Dr. He (Henry) Chen
Guest Editors

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Published Papers (11 papers)

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689 KiB  
Article
An Off-Grid Turbo Channel Estimation Algorithm for Millimeter Wave Communications
by Lingyi Han, Yuexing Peng, Peng Wang and Yonghui Li
Sensors 2016, 16(10), 1562; https://doi.org/10.3390/s16101562 - 22 Sep 2016
Cited by 2 | Viewed by 5051
Abstract
The bandwidth shortage has motivated the exploration of the millimeter wave (mmWave) frequency spectrum for future communication networks. To compensate for the severe propagation attenuation in the mmWave band, massive antenna arrays can be adopted at both the transmitter and receiver to provide [...] Read more.
The bandwidth shortage has motivated the exploration of the millimeter wave (mmWave) frequency spectrum for future communication networks. To compensate for the severe propagation attenuation in the mmWave band, massive antenna arrays can be adopted at both the transmitter and receiver to provide large array gains via directional beamforming. To achieve such array gains, channel estimation (CE) with high resolution and low latency is of great importance for mmWave communications. However, classic super-resolution subspace CE methods such as multiple signal classification (MUSIC) and estimation of signal parameters via rotation invariant technique (ESPRIT) cannot be applied here due to RF chain constraints. In this paper, an enhanced CE algorithm is developed for the off-grid problem when quantizing the angles of mmWave channel in the spatial domain where off-grid problem refers to the scenario that angles do not lie on the quantization grids with high probability, and it results in power leakage and severe reduction of the CE performance. A new model is first proposed to formulate the off-grid problem. The new model divides the continuously-distributed angle into a quantized discrete grid part, referred to as the integral grid angle, and an offset part, termed fractional off-grid angle. Accordingly, an iterative off-grid turbo CE (IOTCE) algorithm is proposed to renew and upgrade the CE between the integral grid part and the fractional off-grid part under the Turbo principle. By fully exploiting the sparse structure of mmWave channels, the integral grid part is estimated by a soft-decoding based compressed sensing (CS) method called improved turbo compressed channel sensing (ITCCS). It iteratively updates the soft information between the linear minimum mean square error (LMMSE) estimator and the sparsity combiner. Monte Carlo simulations are presented to evaluate the performance of the proposed method, and the results show that it enhances the angle detection resolution greatly. Full article
(This article belongs to the Special Issue Millimeter Wave Wireless Communications and Networks)
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Figure 1

Figure 1
<p>Block diagram of structure with beamforming at the base station (BS) and combining at the mobile station (MS).</p>
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<p>Flow chart of the iterative off-grid turbo channel estimation algorithm.</p>
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<p>Flow chart of the improved turbo compressed channel sensing algorithm. FFT and IFFT denote the fast Fourier transform processing and the inverse transform processing, respectively. The modules <math display="inline"> <semantics> <mi mathvariant="bold-italic">D</mi> </semantics> </math> and <math display="inline"> <semantics> <msup> <mi mathvariant="bold-italic">D</mi> <mi>H</mi> </msup> </semantics> </math> denote the transform from <math display="inline"> <semantics> <mi mathvariant="bold-italic">f</mi> </semantics> </math> to <math display="inline"> <semantics> <mi mathvariant="bold-italic">q</mi> </semantics> </math> and the reverse processing.</p>
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<p>The average angle estimation error (AAEE) versus signal-to-noise ratio (SNR) for the proposed algorithm for different values of <span class="html-italic">N</span>.</p>
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<p>The average probability of integral grid point estimation error (APIEE) versus signal-to-noise ratio (SNR) for the proposed algorithm for different values of <span class="html-italic">N</span>.</p>
Full article ">
1557 KiB  
Article
Performance Evaluation of Analog Beamforming with Hardware Impairments for mmW Massive MIMO Communication in an Urban Scenario
by Sonia Gimenez, Sandra Roger, Paolo Baracca, David Martín-Sacristán, Jose F. Monserrat, Volker Braun and Hardy Halbauer
Sensors 2016, 16(10), 1555; https://doi.org/10.3390/s16101555 - 22 Sep 2016
Cited by 17 | Viewed by 7589
Abstract
The use of massive multiple-input multiple-output (MIMO) techniques for communication at millimeter-Wave (mmW) frequency bands has become a key enabler to meet the data rate demands of the upcoming fifth generation (5G) cellular systems. In particular, analog and hybrid beamforming solutions are receiving [...] Read more.
The use of massive multiple-input multiple-output (MIMO) techniques for communication at millimeter-Wave (mmW) frequency bands has become a key enabler to meet the data rate demands of the upcoming fifth generation (5G) cellular systems. In particular, analog and hybrid beamforming solutions are receiving increasing attention as less expensive and more power efficient alternatives to fully digital precoding schemes. Despite their proven good performance in simple setups, their suitability for realistic cellular systems with many interfering base stations and users is still unclear. Furthermore, the performance of massive MIMO beamforming and precoding methods are in practice also affected by practical limitations and hardware constraints. In this sense, this paper assesses the performance of digital precoding and analog beamforming in an urban cellular system with an accurate mmW channel model under both ideal and realistic assumptions. The results show that analog beamforming can reach the performance of fully digital maximum ratio transmission under line of sight conditions and with a sufficient number of parallel radio-frequency (RF) chains, especially when the practical limitations of outdated channel information and per antenna power constraints are considered. This work also shows the impact of the phase shifter errors and combiner losses introduced by real phase shifter and combiner implementations over analog beamforming, where the former ones have minor impact on the performance, while the latter ones determine the optimum number of RF chains to be used in practice. Full article
(This article belongs to the Special Issue Millimeter Wave Wireless Communications and Networks)
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Figure 1

Figure 1
<p>Transceiver considered at the Base Station (BS), which is equipped with <math display="inline"> <semantics> <msub> <mi>N</mi> <mi>t</mi> </msub> </semantics> </math> antenna elements and <span class="html-italic">P</span> radio-frequency (RF) chains.</p>
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<p>Seven-site layout considered for the simulations. Each site covers three <math display="inline"> <semantics> <msup> <mn>120</mn> <mo>∘</mo> </msup> </semantics> </math> sectors, each one equipped with the antenna array boresight indicated by the arrows.</p>
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<p>Cumulative distribution function (CDF) of user throughput for the analog beamforming (ABF) and digital precoding (DP) evaluated schemes.</p>
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<p>CDF of user throughput for the ABF and DP evaluated schemes considering only line of sight (LoS) users.</p>
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<p>CDF of user throughput for the ABF and DP evaluated schemes considering only non line of sight (NLoS) users.</p>
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<p>CDF of user throughput for the ABF with <math display="inline"> <semantics> <mrow> <mi>P</mi> <mo>=</mo> <mn>4</mn> </mrow> </semantics> </math> and digital precoding frequency selective (DP FS) schemes considering different values of <math display="inline"> <semantics> <mrow> <msub> <mi>f</mi> <mi>D</mi> </msub> <mo>Δ</mo> <mi>T</mi> </mrow> </semantics> </math>.</p>
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<p>Average cell throughput for the ABF with <math display="inline"> <semantics> <mrow> <mi>P</mi> <mo>=</mo> <mn>4</mn> </mrow> </semantics> </math> and DP evaluated schemes considering different values of <math display="inline"> <semantics> <mrow> <msub> <mi>f</mi> <mi>D</mi> </msub> <mo>Δ</mo> <mi>T</mi> </mrow> </semantics> </math>.</p>
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<p>CDF of user throughput for the ABF, Maximum Ratio Transmission (MRT) and Equal-Gain Transmission (EGT) evaluated schemes.</p>
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<p>Average cell throughput values for the ABF, MRT and EGT evaluated schemes.</p>
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<p>CDF of user throughput for the ABF scheme with different values of <span class="html-italic">P</span> and <span class="html-italic">L</span>.</p>
Full article ">
8739 KiB  
Article
Proof-of-Concept of a Millimeter-Wave Integrated Heterogeneous Network for 5G Cellular
by Shozo Okasaka, Richard J. Weiler, Wilhelm Keusgen, Andrey Pudeyev, Alexander Maltsev, Ingolf Karls and Kei Sakaguchi
Sensors 2016, 16(9), 1362; https://doi.org/10.3390/s16091362 - 25 Aug 2016
Cited by 33 | Viewed by 11370
Abstract
The fifth-generation mobile networks (5G) will not only enhance mobile broadband services, but also enable connectivity for a massive number of Internet-of-Things devices, such as wireless sensors, meters or actuators. Thus, 5G is expected to achieve a 1000-fold or more increase in capacity [...] Read more.
The fifth-generation mobile networks (5G) will not only enhance mobile broadband services, but also enable connectivity for a massive number of Internet-of-Things devices, such as wireless sensors, meters or actuators. Thus, 5G is expected to achieve a 1000-fold or more increase in capacity over 4G. The use of the millimeter-wave (mmWave) spectrum is a key enabler to allowing 5G to achieve such enhancement in capacity. To fully utilize the mmWave spectrum, 5G is expected to adopt a heterogeneous network (HetNet) architecture, wherein mmWave small cells are overlaid onto a conventional macro-cellular network. In the mmWave-integrated HetNet, splitting of the control plane (CP) and user plane (UP) will allow continuous connectivity and increase the capacity of the mmWave small cells. mmWave communication can be used not only for access linking, but also for wireless backhaul linking, which will facilitate the installation of mmWave small cells. In this study, a proof-of-concept (PoC) was conducted to demonstrate the practicality of a prototype mmWave-integrated HetNet, using mmWave technologies for both backhaul and access. Full article
(This article belongs to the Special Issue Millimeter Wave Wireless Communications and Networks)
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Figure 1

Figure 1
<p>CP/UP splitting in the C-RAN-based HetNet architecture.</p>
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<p>IEEE 802.11ad/WiGig communication devices: (<b>a</b>) Panasonic<sup>®</sup> WiGig-USB dongle: 60-GHz antennas, RF, PHY and MAC components are bundled into one package. Universal Serial Bus (USB)-3.0 is used as the interface to higher layer processors, such as a personal computer (PC). (<b>b</b>) Intel<sup>®</sup> Wireless Gigabit Antenna module (top) and Intel<sup>®</sup> Tri-Band Wireless-AC 17265 WiGig and Wi-Fi + Bluetooth combination module [<a href="#B52-sensors-16-01362" class="html-bibr">52</a>] (bottom). The antenna module contains a beamforming phased antenna array (PAA) of 10 × 2 elements (8 × 2 active elements, 8 in azimuth and 2 in elevation).</p>
Full article ">Figure 3
<p>Example LTE-WLAN coordination and integration architectures: (<b>a</b>) 3GPP/WLAN interworking architecture and (<b>b</b>) LTE-WLAN aggregation.</p>
Full article ">Figure 4
<p>LTE-WLAN interworking architectures in Release 13: (<b>a</b>) LTE-WLAN aggregation (LWA) in a non-collocated scenario and (<b>b</b>) LTE-WLAN radio level integration with IPsec tunnel (LWIP).</p>
Full article ">Figure 5
<p>Static backhaul solution based on reflectarray technology.</p>
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<p>Prototype of the backhaul link installed on a lamp post.</p>
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<p>Highly-directional steerable mmWave antennas: (<b>a</b>) modular antenna array architecture and (<b>b</b>) lens array antenna scheme.</p>
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<p>Constellation diagrams for the backhaul link with an LAA at the TX and RX side.</p>
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<p>LAA prototype link in the field trial.</p>
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<p>Overall illustration of mmWave-integrated HetNet PoC.</p>
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<p>Hardware set-up of HetNet PoC.</p>
Full article ">Figure 12
<p>PoC for LTE-WiGig-integrated HetNet: (<b>a</b>) LTE eNB, RRH and WiGig AP and (<b>b</b>) dual-connectivity UE with LTE and WiGig modules.</p>
Full article ">Figure 13
<p>Protocol stack of LTE-WiGig-integrated HetNet PoC.</p>
Full article ">Figure 14
<p>Experimental setup.</p>
Full article ">Figure 15
<p>Transition of instantaneous UP throughput during LTE-WiGig handover.</p>
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<p>Caching PoC demonstration.</p>
Full article ">Figure 17
<p>Snapshot of small cell on/off (<b>left</b>) and its energy efficiency (<b>right</b>).</p>
Full article ">
6602 KiB  
Article
Channel Measurement and Modeling for 5G Urban Microcellular Scenarios
by Michael Peter, Richard J. Weiler, Barış Göktepe, Wilhelm Keusgen and Kei Sakaguchi
Sensors 2016, 16(8), 1330; https://doi.org/10.3390/s16081330 - 20 Aug 2016
Cited by 15 | Viewed by 7186
Abstract
In order to support the development of channel models for higher frequency bands, multiple urban microcellular measurement campaigns have been carried out in Berlin, Germany, at 60 and 10 GHz. In this paper, the collected data is uniformly analyzed with focus on the [...] Read more.
In order to support the development of channel models for higher frequency bands, multiple urban microcellular measurement campaigns have been carried out in Berlin, Germany, at 60 and 10 GHz. In this paper, the collected data is uniformly analyzed with focus on the path loss (PL) and the delay spread (DS). It reveals that the ground reflection has a dominant impact on the fading behavior. For line-of-sight conditions, the PL exponents are close to free space propagation at 60 GHz, but slightly smaller (1.62) for the street canyon at 10 GHz. The DS shows a clear dependence on the scenario (median values between 16 and 38 ns) and a strong distance dependence for the open square and the wide street canyon. The dependence is less distinct for the narrow street canyon with residential buildings. This behavior is consistent with complementary ray tracing simulations, though the simplified model tends to overestimate the DS. Full article
(This article belongs to the Special Issue Millimeter Wave Wireless Communications and Networks)
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Figure 1

Figure 1
<p>Measurement environment “open square, city center” (OS-CC): (<b>a</b>) photo with transmitter (TX) pole at position Tx3 and (<b>b</b>) map with TX positions and receiver (RX) tracks.</p>
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<p>Top view of 3D models used for ray tracing. (<b>a</b>) OS-CC scenario; (<b>b</b>) “street canyon, city center” (SC-CC) scenario.</p>
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<p>Evolution of averaged power delay profiles (APDPs) over time for TX position Tx1 and mobile RX on Track Rx1 from (<b>a</b>) measurement and (<b>b</b>) simulation.</p>
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<p>Measured and simulated path loss (PL) versus distance with linear regression line; (<b>a</b>) OS-CC scenario; (<b>b</b>) SC-CC scenario.</p>
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<p>Empirical complementary cumulative distribution functions (CCDFs) of the root mean square (RMS) delay spread (DS) for all measured and simulated UMi line-of-sight (LOS) scenarios.</p>
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<p>Measured and simulated DS as a function of distance with linear least-squares (LS) fit: (<b>a</b>) OS-CC scenario; (<b>b</b>) SC-CC scenario.</p>
Full article ">Figure 7
<p>Measured DS as a function of distance with linear LS fit for “street canyon, residential area” (SC-RA) scenario: (<b>a</b>) at 60 GHz; (<b>b</b>) at 10 GHz.</p>
Full article ">
948 KiB  
Article
Beamforming Based Full-Duplex for Millimeter-Wave Communication
by Xiao Liu, Zhenyu Xiao, Lin Bai, Jinho Choi, Pengfei Xia and Xiang-Gen Xia
Sensors 2016, 16(7), 1130; https://doi.org/10.3390/s16071130 - 21 Jul 2016
Cited by 43 | Viewed by 8255
Abstract
In this paper, we study beamforming based full-duplex (FD) systems in millimeter-wave (mmWave) communications. A joint transmission and reception (Tx/Rx) beamforming problem is formulated to maximize the achievable rate by mitigating self-interference (SI). Since the optimal solution is difficult to find due to [...] Read more.
In this paper, we study beamforming based full-duplex (FD) systems in millimeter-wave (mmWave) communications. A joint transmission and reception (Tx/Rx) beamforming problem is formulated to maximize the achievable rate by mitigating self-interference (SI). Since the optimal solution is difficult to find due to the non-convexity of the objective function, suboptimal schemes are proposed in this paper. A low-complexity algorithm, which iteratively maximizes signal power while suppressing SI, is proposed and its convergence is proven. Moreover, two closed-form solutions, which do not require iterations, are also derived under minimum-mean-square-error (MMSE), zero-forcing (ZF), and maximum-ratio transmission (MRT) criteria. Performance evaluations show that the proposed iterative scheme converges fast (within only two iterations on average) and approaches an upper-bound performance, while the two closed-form solutions also achieve appealing performances, although there are noticeable differences from the upper bound depending on channel conditions. Interestingly, these three schemes show different robustness against the geometry of Tx/Rx antenna arrays and channel estimation errors. Full article
(This article belongs to the Special Issue Millimeter Wave Wireless Communications and Networks)
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Figure 1
<p>Illustration of the FD mmWave communication system.</p>
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<p>The transmit and receive antenna arrays of a node.</p>
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<p>JAR and convergence performances of ZF-Max-Power with random initial transmit AWVs (<b>Left</b>: LOS channel, <b>Right</b>: NLOS channel). <math display="inline"> <semantics> <mrow> <msub> <mi>ε</mi> <mn>11</mn> </msub> <mo>=</mo> <msub> <mi>ε</mi> <mn>22</mn> </msub> <mo>=</mo> <mn>40</mn> </mrow> </semantics> </math> dB. For LOS channel, <math display="inline"> <semantics> <mrow> <msub> <mi>ε</mi> <mn>12</mn> </msub> <mo>=</mo> <msub> <mi>ε</mi> <mn>21</mn> </msub> <mo>=</mo> <mn>20</mn> </mrow> </semantics> </math> dB, while for NLOS channel, <math display="inline"> <semantics> <mrow> <msub> <mi>ε</mi> <mn>12</mn> </msub> <mo>=</mo> <msub> <mi>ε</mi> <mn>21</mn> </msub> <mo>=</mo> <mn>10</mn> </mrow> </semantics> </math> dB. For the case of separate arrays, <math display="inline"> <semantics> <mrow> <mi>d</mi> <mo>/</mo> <mi>λ</mi> <mo>=</mo> <mn>1</mn> </mrow> </semantics> </math> and <math display="inline"> <semantics> <mrow> <mi>ω</mi> <mo>=</mo> <mi>π</mi> <mo>/</mo> <mn>6</mn> </mrow> </semantics> </math> rad, while for the case of sharing the same array, <math display="inline"> <semantics> <mrow> <mi>d</mi> <mo>/</mo> <mi>λ</mi> <mo>=</mo> <mn>0</mn> </mrow> </semantics> </math> and <math display="inline"> <semantics> <mrow> <mi>ω</mi> <mo>=</mo> <mn>0</mn> </mrow> </semantics> </math> rad.</p>
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<p>JAR performance of the involved schemes with respect to varying <span class="html-italic">ω</span> under LOS (<b>Left</b>) and NLOS (<b>Right</b>) channels in the case of separate arrays. <math display="inline"> <semantics> <mrow> <msub> <mi>ε</mi> <mn>11</mn> </msub> <mo>=</mo> <msub> <mi>ε</mi> <mn>22</mn> </msub> <mo>=</mo> <mn>40</mn> </mrow> </semantics> </math> dB, <math display="inline"> <semantics> <mrow> <msub> <mi>ε</mi> <mn>12</mn> </msub> <mo>=</mo> <msub> <mi>ε</mi> <mn>21</mn> </msub> <mo>=</mo> <mn>10</mn> </mrow> </semantics> </math> dB, <math display="inline"> <semantics> <mrow> <mi>d</mi> <mo>/</mo> <mi>λ</mi> <mo>=</mo> <mn>2</mn> </mrow> </semantics> </math>. For LB-MMSE, the JAR with <math display="inline"> <semantics> <mrow> <mi>d</mi> <mo>/</mo> <mi>λ</mi> <mo>=</mo> <mn>10</mn> </mrow> </semantics> </math> is also plotted.</p>
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<p>JAR performance of the involved schemes with respect to varying <span class="html-italic">d</span> under LOS channel in the case of separate arrays. <math display="inline"> <semantics> <mrow> <mi>ω</mi> <mo>=</mo> <mi>π</mi> </mrow> </semantics> </math> rad. In the (<b>Left</b>) hand figure SI is assumed fixed, i.e., <math display="inline"> <semantics> <mrow> <msub> <mi>ε</mi> <mn>11</mn> </msub> <mo>=</mo> <msub> <mi>ε</mi> <mn>22</mn> </msub> <mo>=</mo> <mn>40</mn> </mrow> </semantics> </math> dB, <math display="inline"> <semantics> <mrow> <msub> <mi>ε</mi> <mn>12</mn> </msub> <mo>=</mo> <msub> <mi>ε</mi> <mn>21</mn> </msub> <mo>=</mo> <mn>10</mn> </mrow> </semantics> </math> dB; while in the (<b>Right</b>) hand figure SI varies with <math display="inline"> <semantics> <mrow> <mi>d</mi> <mo>/</mo> <mi>λ</mi> </mrow> </semantics> </math>, i.e., <math display="inline"> <semantics> <mrow> <msub> <mi>ε</mi> <mn>11</mn> </msub> <mo>=</mo> <msub> <mi>ε</mi> <mn>22</mn> </msub> <mo>=</mo> <mn>60</mn> <mo>−</mo> <mn>20</mn> <msub> <mo form="prefix">log</mo> <mn>10</mn> </msub> <mrow> <mo>(</mo> <mi>d</mi> <mo>/</mo> <mi>λ</mi> <mo>)</mo> </mrow> </mrow> </semantics> </math> dB, <math display="inline"> <semantics> <mrow> <msub> <mi>ε</mi> <mn>12</mn> </msub> <mo>=</mo> <msub> <mi>ε</mi> <mn>21</mn> </msub> <mo>=</mo> <mn>10</mn> </mrow> </semantics> </math> dB.</p>
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<p>JAR comparison between different array settings (separate arrays versus the same array) under LOS (<b>Left</b>) and NLOS (<b>Right</b>) channels with varying SI. <math display="inline"> <semantics> <mrow> <msub> <mi>ε</mi> <mn>12</mn> </msub> <mo>=</mo> <msub> <mi>ε</mi> <mn>21</mn> </msub> <mo>=</mo> <mn>10</mn> </mrow> </semantics> </math> dB. For the case of separate arrays, <math display="inline"> <semantics> <mrow> <mi>ω</mi> <mo>=</mo> <mn>0.6</mn> <mi>π</mi> </mrow> </semantics> </math> rad, <math display="inline"> <semantics> <mrow> <mi>d</mi> <mo>/</mo> <mi>λ</mi> <mo>=</mo> <mn>1</mn> </mrow> </semantics> </math>.</p>
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<p>Effects of channel estimation errors on the proposed schemes with separate arrays under LOS ( <b>Left</b>) and NLOS (<b>Right</b>) channels. <math display="inline"> <semantics> <mrow> <msub> <mi>ε</mi> <mn>12</mn> </msub> <mo>=</mo> <msub> <mi>ε</mi> <mn>21</mn> </msub> <mo>=</mo> <mn>10</mn> </mrow> </semantics> </math> dB, <math display="inline"> <semantics> <mrow> <msub> <mi>ε</mi> <mn>11</mn> </msub> <mo>=</mo> <msub> <mi>ε</mi> <mn>22</mn> </msub> <mo>=</mo> <mn>40</mn> </mrow> </semantics> </math> dB, <math display="inline"> <semantics> <mrow> <mi>ω</mi> <mo>=</mo> <mi>π</mi> </mrow> </semantics> </math> rad, <math display="inline"> <semantics> <mrow> <mi>d</mi> <mo>/</mo> <mi>λ</mi> <mo>=</mo> <mn>1</mn> </mrow> </semantics> </math>.</p>
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<p>Effects of AWV error and EVM error on the JAR performance of ZF-Max-Power under LOS (<b>Left</b>) and NLOS (<b>Right</b>) channels. <math display="inline"> <semantics> <mrow> <msub> <mi>ε</mi> <mn>12</mn> </msub> <mo>=</mo> <msub> <mi>ε</mi> <mn>21</mn> </msub> <mo>=</mo> <mn>10</mn> </mrow> </semantics> </math> dB, <math display="inline"> <semantics> <mrow> <msub> <mi>ε</mi> <mn>11</mn> </msub> <mo>=</mo> <msub> <mi>ε</mi> <mn>22</mn> </msub> <mo>=</mo> <mn>50</mn> </mrow> </semantics> </math> dB, <math display="inline"> <semantics> <mrow> <mi>ω</mi> <mo>=</mo> <mn>0.8</mn> <mi>π</mi> </mrow> </semantics> </math> rad, <math display="inline"> <semantics> <mrow> <mi>d</mi> <mo>/</mo> <mi>λ</mi> <mo>=</mo> <mn>1</mn> </mrow> </semantics> </math>.</p>
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2368 KiB  
Article
Efficient Preamble Design Technique for Millimeter-Wave Cellular Systems with Beamforming
by Dae Geun Han, Yeong Jun Kim and Yong Soo Cho
Sensors 2016, 16(7), 1129; https://doi.org/10.3390/s16071129 - 21 Jul 2016
Cited by 2 | Viewed by 5988
Abstract
The processing time for beam training in millimeter-wave (mmWave) cellular systems can be significantly reduced by a code division multiplexing (CDM)-based technique, where multiple beams are transmitted simultaneously with their corresponding Tx beam IDs (BIDs) in the preamble. However, mmWave cellular systems with [...] Read more.
The processing time for beam training in millimeter-wave (mmWave) cellular systems can be significantly reduced by a code division multiplexing (CDM)-based technique, where multiple beams are transmitted simultaneously with their corresponding Tx beam IDs (BIDs) in the preamble. However, mmWave cellular systems with CDM-based preambles require a large number of cell IDs (CIDs) and BIDs, and a high computational complexity for CID and BID (CBID) searches. In this paper, a new preamble design technique that can increase the number of CBIDs significantly is proposed, using a preamble sequence constructed by a combination of two Zadoff-Chu (ZC) sequences. An efficient technique for the CBID detection is also described for the proposed preamble. It is shown by simulations using a simple model of an mmWave cellular system that the proposed technique can obtain a significant reduction in the complexity of the CBID detection without a noticeable performance degradation, compared to the previous technique. Full article
(This article belongs to the Special Issue Millimeter Wave Wireless Communications and Networks)
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<p>Concept of the preamble generation in the proposed technique.</p>
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<p>Example of an mmWave cellular system.</p>
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<p>Preamble structure in the proposed technique.</p>
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<p>Correlation properties of the proposed preamble depending on the value of <math display="inline"> <semantics> <mrow> <msub> <mi>N</mi> <mi>r</mi> </msub> </mrow> </semantics> </math>: (<b>a</b>) Type-1; (<b>b</b>) Type-2.</p>
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<p>Success probability of the CBID detection in one-cell and two-cell environments: (<b>a</b>) 8 <math display="inline"> <semantics> <mrow> <mo>×</mo> </mrow> </semantics> </math> 8; (<b>b</b>) 8 <math display="inline"> <semantics> <mrow> <mo>×</mo> </mrow> </semantics> </math> 1; (<b>c</b>) 8 <math display="inline"> <semantics> <mrow> <mo>×</mo> </mrow> </semantics> </math> 1.</p>
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<p>BER performance in one-cell and two-cell environments.</p>
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<p>Number of complex multiplications required for the CBID detection when <math display="inline"> <semantics> <mrow> <msub> <mi>N</mi> <mi>C</mi> </msub> </mrow> </semantics> </math> varies.</p>
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4278 KiB  
Article
First Eigenmode Transmission by High Efficient CSI Estimation for Multiuser Massive MIMO Using Millimeter Wave Bands
by Kazuki Maruta, Tatsuhiko Iwakuni, Atsushi Ohta, Takuto Arai, Yushi Shirato, Satoshi Kurosaki and Masataka Iizuka
Sensors 2016, 16(7), 1051; https://doi.org/10.3390/s16071051 - 8 Jul 2016
Cited by 9 | Viewed by 6420
Abstract
Drastic improvements in transmission rate and system capacity are required towards 5th generation mobile communications (5G). One promising approach, utilizing the millimeter wave band for its rich spectrum resources, suffers area coverage shortfalls due to its large propagation loss. Fortunately, massive multiple-input multiple-output [...] Read more.
Drastic improvements in transmission rate and system capacity are required towards 5th generation mobile communications (5G). One promising approach, utilizing the millimeter wave band for its rich spectrum resources, suffers area coverage shortfalls due to its large propagation loss. Fortunately, massive multiple-input multiple-output (MIMO) can offset this shortfall as well as offer high order spatial multiplexing gain. Multiuser MIMO is also effective in further enhancing system capacity by multiplexing spatially de-correlated users. However, the transmission performance of multiuser MIMO is strongly degraded by channel time variation, which causes inter-user interference since null steering must be performed at the transmitter. This paper first addresses the effectiveness of multiuser massive MIMO transmission that exploits the first eigenmode for each user. In Line-of-Sight (LoS) dominant channel environments, the first eigenmode is chiefly formed by the LoS component, which is highly correlated with user movement. Therefore, the first eigenmode provided by a large antenna array can improve the robustness against the channel time variation. In addition, we propose a simplified beamforming scheme based on high efficient channel state information (CSI) estimation that extracts the LoS component. We also show that this approximate beamforming can achieve throughput performance comparable to that of the rigorous first eigenmode transmission. Our proposed multiuser massive MIMO scheme can open the door for practical millimeter wave communication with enhanced system capacity. Full article
(This article belongs to the Special Issue Millimeter Wave Wireless Communications and Networks)
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<p>System model: (<b>a</b>) Multistream transmission per user equipment (UE): <span class="html-italic">Nu</span> = 4 and <span class="html-italic">Ns</span> = 4; and (<b>b</b>) 1st eigenmode transmission per UE: <span class="html-italic">Nu</span> = 16 and <span class="html-italic">Ns</span> = 1.</p>
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<p>Channel time variation: (<b>a</b>) channel correlation fluctuation of four eigenmodes when <span class="html-italic">Nr</span> = 16; and (<b>b</b>) channel correlation of the 1st eigenmode with increased number of UE antenna elements, <span class="html-italic">Nr</span>.</p>
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<p>Proposed high efficient channel state information (CSI) estimation.</p>
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<p>Time variant characteristics within the CSI estimation period. Case 1: <span class="html-italic">Nu</span> = 4, <span class="html-italic">Ns</span> = 4; Case 2: <span class="html-italic">Nu</span> = 16, <span class="html-italic">Ns</span> = 1. (<b>a</b>) Average SINR per stream versus elapsed time. (<b>b</b>) Average throughput per stream versus elapsed time.</p>
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<p>Cumulative distribution functions (CDFs) of SINR per signal stream.</p>
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<p>CDFs of throughput per signal stream.</p>
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<p>CDFs of UE throughput.</p>
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<p>CDFs of System throughput.</p>
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<p>Average system throughput versus UE speed.</p>
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<p>Average system throughput versus number of multiplexed UEs.</p>
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<p>Average beamforming gain versus signal-to-noise power ratio (SNR).</p>
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932 KiB  
Article
Content-Based Multi-Channel Network Coding Algorithm in the Millimeter-Wave Sensor Network
by Kai Lin, Di Wang and Long Hu
Sensors 2016, 16(7), 1023; https://doi.org/10.3390/s16071023 - 1 Jul 2016
Cited by 1 | Viewed by 4980
Abstract
With the development of wireless technology, the widespread use of 5G is already an irreversible trend, and millimeter-wave sensor networks are becoming more and more common. However, due to the high degree of complexity and bandwidth bottlenecks, the millimeter-wave sensor network still faces [...] Read more.
With the development of wireless technology, the widespread use of 5G is already an irreversible trend, and millimeter-wave sensor networks are becoming more and more common. However, due to the high degree of complexity and bandwidth bottlenecks, the millimeter-wave sensor network still faces numerous problems. In this paper, we propose a novel content-based multi-channel network coding algorithm, which uses the functions of data fusion, multi-channel and network coding to improve the data transmission; the algorithm is referred to as content-based multi-channel network coding (CMNC). The CMNC algorithm provides a fusion-driven model based on the Dempster-Shafer (D-S) evidence theory to classify the sensor nodes into different classes according to the data content. By using the result of the classification, the CMNC algorithm also provides the channel assignment strategy and uses network coding to further improve the quality of data transmission in the millimeter-wave sensor network. Extensive simulations are carried out and compared to other methods. Our simulation results show that the proposed CMNC algorithm can effectively improve the quality of data transmission and has better performance than the compared methods. Full article
(This article belongs to the Special Issue Millimeter Wave Wireless Communications and Networks)
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<p>Different methods to transmit data with millimeter-wave technology. (<b>a</b>) Traditional transmission method with random channel assignment; (<b>b</b>) the transmission using the content-based multi-channel network coding (CMNC) algorithm.</p>
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<p>Uncertainty representation of the information.</p>
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<p>Example with a broadcast source and three receiver sensor nodes.</p>
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<p>The round of the classification period and transmission period.</p>
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<p>The error rate of the fusion-driven model based on Dempster–Shafer (D-S) evidence theory with different training set numbers.</p>
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<p>The relationship between the throughput and the number of sensor nodes.</p>
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<p>The relationship between the average transmission cost and the number of sensor nodes.</p>
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653 KiB  
Article
Mobility-Aware Caching and Computation Offloading in 5G Ultra-Dense Cellular Networks
by Min Chen, Yixue Hao, Meikang Qiu, Jeungeun Song, Di Wu and Iztok Humar
Sensors 2016, 16(7), 974; https://doi.org/10.3390/s16070974 - 25 Jun 2016
Cited by 150 | Viewed by 13290
Abstract
Recent trends show that Internet traffic is increasingly dominated by content, which is accompanied by the exponential growth of traffic. To cope with this phenomena, network caching is introduced to utilize the storage capacity of diverse network devices. In this paper, we first [...] Read more.
Recent trends show that Internet traffic is increasingly dominated by content, which is accompanied by the exponential growth of traffic. To cope with this phenomena, network caching is introduced to utilize the storage capacity of diverse network devices. In this paper, we first summarize four basic caching placement strategies, i.e., local caching, Device-to-Device (D2D) caching, Small cell Base Station (SBS) caching and Macrocell Base Station (MBS) caching. However, studies show that so far, much of the research has ignored the impact of user mobility. Therefore, taking the effect of the user mobility into consideration, we proposes a joint mobility-aware caching and SBS density placement scheme (MS caching). In addition, differences and relationships between caching and computation offloading are discussed. We present a design of a hybrid computation offloading and support it with experimental results, which demonstrate improved performance in terms of energy cost. Finally, we discuss the design of an incentive mechanism by considering network dynamics, differentiated user’s quality of experience (QoE) and the heterogeneity of mobile terminals in terms of caching and computing capabilities. Full article
(This article belongs to the Special Issue Millimeter Wave Wireless Communications and Networks)
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<p>Illustration of the protocol for content access.</p>
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<p>Illustration of the result of caching placement. (<b>a</b>) The impact of <span class="html-italic">ρ</span> on the probability that users can get content; (<b>b</b>) the impact of <span class="html-italic">λ</span> on the probability that users can get content.</p>
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<p>Illustration of the content caching placement. (<b>a</b>) Case of low user mobiliity; (<b>b</b>) Case of high user mobiliity.</p>
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<p>Illustration of the hybrid computation offloading: (<b>a</b>) Device-to-Device (D2D) computing result feedback; (<b>b</b>) Small cell Base Station (SBS) computing result feedback; (<b>c</b>) Macrocell Base Station (MBS) computing result feedback.</p>
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<p>Illustration of the computation offloading energy cost. (<b>a</b>) Comparing the energy cost of MBS, SBS and hybrid computation offloading; (<b>b</b>) comparing the energy cost of MBS, D2D and hybrid computation offloading.</p>
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574 KiB  
Article
Millimetre-Wave Backhaul for 5G Networks: Challenges and Solutions
by Wei Feng, Yong Li, Depeng Jin, Li Su and Sheng Chen
Sensors 2016, 16(6), 892; https://doi.org/10.3390/s16060892 - 16 Jun 2016
Cited by 92 | Viewed by 14560
Abstract
The trend for dense deployment in future 5G mobile communication networks makes current wired backhaul infeasible owing to the high cost. Millimetre-wave (mm-wave) communication, a promising technique with the capability of providing a multi-gigabit transmission rate, offers a flexible and cost-effective candidate for [...] Read more.
The trend for dense deployment in future 5G mobile communication networks makes current wired backhaul infeasible owing to the high cost. Millimetre-wave (mm-wave) communication, a promising technique with the capability of providing a multi-gigabit transmission rate, offers a flexible and cost-effective candidate for 5G backhauling. By exploiting highly directional antennas, it becomes practical to cope with explosive traffic demands and to deal with interference problems. Several advancements in physical layer technology, such as hybrid beamforming and full duplexing, bring new challenges and opportunities for mm-wave backhaul. This article introduces a design framework for 5G mm-wave backhaul, including routing, spatial reuse scheduling and physical layer techniques. The associated optimization model, open problems and potential solutions are discussed to fully exploit the throughput gain of the backhaul network. Extensive simulations are conducted to verify the potential benefits of the proposed method for the 5G mm-wave backhaul design. Full article
(This article belongs to the Special Issue Millimeter Wave Wireless Communications and Networks)
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<p>System overview for 5G mm-wave backhauling.</p>
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<p>Physical layer techniques: hybrid beamforming and full duplexing.</p>
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<p>System framework for 5G mm-wave backhauling.</p>
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<p>(<b>a</b>) Routing results of the shortest path algorithm and the capacity optimization method in the mm-wave backhaul network; and (<b>b</b>) the scheduling scheme in four scenarios based on the optimization routing results in (<b>a</b>) in a mm-wave backhaul network.</p>
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<p>(<b>a</b>) Channel parameter settings and (<b>b</b>–<b>d</b>) the performance of the throughput, delay and packet loss rate of five schemes, respectively (HBF, BF, HDP and FDP refer to hybrid beamforming, analogue beamforming, half-duplex and full-duplex, respectively, while non-STDMA is the scheme that does not adopt spatial reuse at all).</p>
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3772 KiB  
Article
Asymmetric Directional Multicast for Capillary Machine-to-Machine Using mmWave Communications
by Jung-Hyok Kwon and Eui-Jik Kim
Sensors 2016, 16(4), 515; https://doi.org/10.3390/s16040515 - 11 Apr 2016
Cited by 9 | Viewed by 4772
Abstract
The huge demand for high data rate machine-to-machine (M2M) services has led to the use of millimeter Wave (mmWave) band communications with support for a multi-Gbps data rate through the use of directional antennas. However, unnecessary sector switching in multicast transmissions with directional [...] Read more.
The huge demand for high data rate machine-to-machine (M2M) services has led to the use of millimeter Wave (mmWave) band communications with support for a multi-Gbps data rate through the use of directional antennas. However, unnecessary sector switching in multicast transmissions with directional antennas results in a long delay, and consequently a low throughput. We propose asymmetric directional multicast (ADM) for capillary M2M to address this problem in mmWave communications. ADM provides asymmetric sectorization that is optimized for the irregular deployment pattern of mulicast group members. In ADM, an M2M gateway builds up asymmetric sectors with a beamwidth of a different size to cover all multicast group members with the minimum number of directional transmissions. The performance of ADM under various simulation environments is evaluated through a comparison with legacy mmWave multicast. The results of the simulation indicate that ADM achieves a better performance in terms of the transmission sectors, the transmission time, and the aggregate throughput when compared with the legacy multicast method. Full article
(This article belongs to the Special Issue Millimeter Wave Wireless Communications and Networks)
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<p>Two-dimensional flat-top directional antenna model.</p>
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<p>Coverage region.</p>
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<p>Example of asymmetric sectorization.</p>
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<p>Number of transmission sectors for various unit-beam sectors.</p>
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<p>Number of transmission sectors for various room sizes.</p>
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<p>Transmission time for various unit-beam sectors.</p>
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<p>Transmission time for various room shapes.</p>
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<p>Aggregate throughput for various unit-beam sectors.</p>
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<p>Aggregate throughput for various room shapes.</p>
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<p>Aggregate throughput for various positions of M2M GW.</p>
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<p>Energy consumption per device for control message exchange.</p>
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<p>Transmission time for control message exchange.</p>
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<p>Number of received packets per multicast group.</p>
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<p>Variation of fairness index for various numbers of packets per multicast group.</p>
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