In-band-full-duplex integrated access and backhaul enabled next generation wireless networks

In sixth generation (6G) wireless networks, the severe traffic congestion in the microwave frequencies motivates the exploration of the large available bandwidth in the millimetre-wave (mmWave) frequencies to achieve higher network capacity and data rate. Since large-scale antenna arrays and dense base station deployment are required, the hybrid beamforming architecture and the recently proposed integrated access and backhaul (IAB) networks become potential candidates for providing cost and hardware-friendly techniques for 6G wireless networks. In addition, in-band-full-duplex (IBFD) has been recently paid much more research attention since it can make the transmission and reception occur in the same time and frequency band, which nearly doubles the communication spectral efficiency (SE) compared with state-of-the-art half-duplex (HD) systems. Since 6G will explore sensing as its new capability, future wireless networks can go far beyond communications. Motivated by this, the development of integrated sensing and communications (ISAC) systems, where radar and communication systems share the same spectrum resources and hardware, has become one of the major goals in 6G. This PhD thesis focuses on the design and analysis of IBFD-IAB wireless networks in the frequency range 2 (FR2) band (≥ 24.250 GHz) at mmWave frequencies for the potential use in 6G. Firstly, we develop a novel design for the single-cell FR2-IBFD-IAB networks with subarray-based hybrid beamforming, which can enhance the SE and coverage while reducing the latency. The radio frequency (RF) beamformers are obtained via RF codebooks given by a modified matrix-wise Linde-Buzo-Gray (LBG) algorithm. The self-interference (SI) is cancelled in three stages, where the first stage of antenna isolation is assumed to be successfully deployed. The second stage consists of the optical domain-based RF cancellation, where cancellers are connected with the RF chain pairs. The third stage is comprised of the digital cancellation via successive interference cancellation followed by minimum mean-squared error (MSE) baseband receiver. Multiuser interference in the access link is cancelled by zero-forcing at the IAB-node transmitter. The proposed codebook algorithm avoids undesirable low-rank behaviour, while the proposed staged-SI cancellation (SIC) shows satisfactory cancellation performance in the wideband IBFD scenario. However, the system performance can be affected by the hardware impairments (HWI) and RF effective channel estimation errors. Secondly, we study an FR2-IBFD-ISAC-IAB network for vehicle-to-everything communications, where the IAB-node acts as a roadside unit performing sensing and communication simultaneously (i.e., at the same time and frequency band). The SI due to the IBFD operation will be cancelled in the propagation, analogue, and digital domains; only the residual SI (RSI) is reserved for performance analysis. Considering the subarray-based hybrid beamforming structure, including HWI and RF effective SI channel estimation error, the unscented Kalman filter is used for tracking multiple vehicles in the studied scenario. The proposed system shows an enhanced SE compared with the HD system, and the tracking MSEs averaged across all vehicles of each state parameter are close to their posterior Cramér-Rao lower bounds. Thirdly, we analyse the performance of the multi-cell wideband single-hop backhaul FR2-IBFD-IAB networks by using stochastic geometry analysis. We model the wired-connected next generation NodeBs (gNBs) as the Matérn hard-core point process (MHCPP) to meet the real-world deployment requirement and reduce the cost caused by wired connection in the network. We first derive association probabilities that reflect how likely the typical user-equipment is served by a gNB or an IAB-node based on the maximum long-term averaged biased-received-desired-signal power criteria. Further, by leveraging the composite Gamma-Lognormal distribution, we derive results for the signal to interference plus noise ratio coverage, capacity with outage, and ergodic capacity of the network. In order to assess the impact of noise, we consider the sidelobe gain on inter-cell interference links and the analogue to digital converter quantization noise. Compared with the HD transmission, the designated system shows an enhanced capacity when the SIC operates successfully. We also study how the power bias and density ratio of the IAB-node to gNB, and the hard-core distance can affect system performance. Overall, this thesis aims to contribute to the research efforts of shaping the 6G wireless networks by designing and analysing the FR2-IBFD-IAB inspired networks in the FR2 band at mmWave frequencies that will be potentially used in 6G for both communication only and ISAC scenarios

Index Modulation Techniques for Energy-efficient Transmission in Large-scale MIMO Systems

This thesis exploits index modulation techniques to design energy- and spectrum-efficient system models to operate in future wireless networks. In this respect, index modulation techniques are studied considering two different media: mapping the information onto the frequency indices of multicarrier systems, and onto the antenna array indices of a platform that comprises multiple antennas. The index modulation techniques in wideband communication scenarios considering orthogonal and generalized frequency division multiplexing systems are studied first. Single cell multiuser networks are considered while developing the system models that exploit the index modulation on the subcarriers of the multicarrier systems. Instead of actively modulating all the subcarriers, a subset is selected according to the index modulation bits. As a result, there are subcarriers that remain idle during the data transmission phase and the activation pattern of the subcarriers convey additional information. The transceivers for the orthogonal and generalized frequency division multiplexing systems with index modulation are both designed considering the uplink and downlink transmission phases with a linear combiner and precoder in order to reduce the system complexity. In the developed system models, channel state information is required only at the base station. The linear combiner is designed adopting minimum mean square error method to mitigate the inter-user-interference. The proposed system models offer a flexible design as the parameters are independent of each other. The parameters can be adjusted to design the system in favor of the energy efficiency, spectrum efficiency, peak-to-average power ratio, or error performance. Then, the index modulation techniques are studied for large-scale multiple-input multiple-output systems that operate in millimeter wave bands. In order to overcome the drawbacks of transmission in millimeter wave frequencies, channel properties should be taken in to account while envisaging the wireless communication network. The large-scale multiple-input multiple-output systems increase the degrees of freedom in the spatial domain. This feature can be exploited to focus the transmit power directly onto the intended receiver terminal to cope with the severe path-loss. However, scaling up the number of hardware elements results in excessive power consumption. Hybrid architectures provide a remedy by shifting a part of the signal processing to the analog domain. In this way, the number of bulky and high power consuming hardware elements can be reduced. However, there will be a performance degradation as a consequence of renouncing the fully digital signal processing. Index modulation techniques can be combined with the hybrid system architecture to compensate the loss in spectrum efficiency to further increase the data rates. A user terminal architecture is designed that employs analog beamforming together with spatial modulation where a part of the information bits is mapped onto the indices of the antenna arrays. The system is comprised a switching stage that allocates the user terminal antennas on the phase shifter groups to minimize the spatial correlation, and a phase shifting stage that maximizes the beamforming gain to combat the path-loss. A computationally efficient optimization algorithm is developed to configure the system. The flexibility of the architecture enables optimization of the hybrid transceiver at any signal-to-noise ratio values. A base station is designed in which hybrid beamforming together with spatial modulation is employed. The analog beamformer is designed to point the transmit beam only in the direction of the intended user terminal to mitigate leakage of the transmit power to other directions. The analog beamformer to transmit the signal is chosen based on the spatial modulation bits. The digital precoder is designed to eliminate the inter-user-interference by exploiting the zero-forcing method. The base station computes the hybrid beamformers and the digital combiners, and only feeds back the digital combiners of each antenna array-user pair to the related user terminals. Thus, a low complexity user architecture is sufficient to achieve a higher performance. The developed optimization framework for the energy efficiency jointly optimizes the number of served users and the total transmit power by utilizing the derived upper bound of the achievable rate. The proposed transceiver architectures provide a more energy-efficient system model compared to the hybrid systems in which the spatial modulation technique is not exploited. This thesis develops low-complexity system models that operate in narrowband and wideband channel environments to meet the energy and spectrum efficiency demands of future wireless networks. It is corroborated in the thesis that adopting index modulation techniques both in the systems improves the system performance in various aspects.:1 Introduction 1 1.1 Motivation 1 1.2 Overview and Contribution 2 1.3 Outline 9 2 Preliminaries and Fundamentals 13 2.1 Multicarrier Systems 13 2.2 Large-scale Multiple Input Multiple Output Systems 17 2.3 Index Modulation Techniques 19 2.4 Single Cell Multiuser Networks 22 3 Multicarrier Systems with Index Modulation 27 3.1 Orthogonal Frequency Division Multiplexing 28 3.2 Generalized Frequency Division Multiplexing 40 3.3 Summary 52 4 Hybrid Beamforming with Spatial Modulation 55 4.1 Uplink Transmission 56 4.2 Downlink Transmission 74 4.3 Summary 106 5 Conclusion and Outlook 109 5.1 Conclusion 109 5.2 Outlook 111 A Quantization Error Derivations 113 B On the Achievable Rate of Gaussian Mixtures 115 B.1 The Conditional Density Function 115 B.2 Tight Bounds on the Differential Entropy 116 B.3 A Bound on the Achievable Rate 118 C Multiuser MIMO Downlink without Spatial Modulation 121 Bibliograph

Enabling Efficient Communications Over Millimeter Wave Massive MIMO Channels Using Hybrid Beamforming

The use of massive multiple-input multiple-output (MIMO) over millimeter wave (mmWave) channels is the new frontier for fulfilling the exigent requirements of next-generation wireless systems and solving the wireless network impending crunch. Massive MIMO systems and mmWave channels offer larger numbers of antennas, higher carrier frequencies, and wider signaling bandwidths. Unleashing the full potentials of these tremendous degrees of freedom (dimensions) hinges on the practical deployment of those technologies. Hybrid analog and digital beamforming is considered as a stepping-stone to the practical deployment of mmWave massive MIMO systems since it significantly reduces their operating and implementation costs, energy consumption, and system design complexity. The prevalence of adopting mmWave and massive MIMO technologies in next-generation wireless systems necessitates developing agile and cost-efficient hybrid beamforming solutions that match the various use-cases of these systems. In this thesis, we propose hybrid precoding and combining solutions that are tailored to the needs of these specific cases and account for the main limitations of hybrid processing. The proposed solutions leverage the sparsity and spatial correlation of mmWave massive MIMO channels to reduce the feedback overhead and computational complexity of hybrid processing. Real-time use-cases of next-generation wireless communication, including connected cars, virtual-reality/augmented-reality, and high definition video transmission, require high-capacity and low-latency wireless transmission. On the physical layer level, this entails adopting near capacity-achieving transmission schemes with very low computational delay. Motivated by this, we propose low-complexity hybrid precoding and combining schemes for massive MIMO systems with partially and fully-connected antenna array structures. Leveraging the disparity in the dimensionality of the analog and the digital processing matrices, we develop a two-stage channel diagonalization design approach in order to reduce the computational complexity of the hybrid precoding and combining while maintaining high spectral efficiency. Particularly, the analog processing stage is designed to maximize the antenna array gain in order to avoid performing computationally intensive operations such as matrix inversion and singular value decomposition in high dimensions. On the other hand, the low-dimensional digital processing stage is designed to maximize the spectral efficiency of the systems. Computational complexity analysis shows that the proposed schemes offer significant savings compared to prior works where asymptotic computational complexity reductions ranging between $80\%$ and $98\%$. Simulation results validate that the spectral efficiency of the proposed schemes is near-optimal where in certain scenarios the signal-to-noise-ratio (SNR) gap to the optimal fully-digital spectral efficiency is less than $1$ dB. On the other hand, integrating mmWave and massive MIMO into the cellular use-cases requires adopting hybrid beamforming schemes that utilize limited channel state information at the transmitter (CSIT) in order to adapt the transmitted signals to the current channel. This is so mainly because obtaining perfect CSIT in frequency division duplexing (FDD) architecture, which dominates the cellular systems, poses serious concerns due to its large training and excessive feedback overhead. Motivated by this, we develop low-overhead hybrid precoding algorithms for selecting the baseband digital and radio frequency (RF) analog precoders from statistically skewed DFT-based codebooks. The proposed algorithms aim at maximizing the spectral efficiency based on minimizing the chordal distance between the optimal unconstrained precoder and the hybrid beamformer and maximizing the signal to interference noise ratio for the single-user and multi-user cases, respectively. Mathematical analysis shows that the proposed algorithms are asymptotically optimal as the number of transmit antennas goes to infinity and the mmWave channel has a limited number of paths. Moreover, it shows that the performance gap between the lower and upper bounds depends heavily on how many DFT columns are aligned to the largest eigenvectors of the transmit antenna array response of the mmWave channel or equivalently the transmit channel covariance matrix when only the statistical channel knowledge is available at the transmitter. Further, we verify the performance of the proposed algorithms numerically where the obtained results illustrate that the spectral efficiency of the proposed algorithms can approach that of the optimal precoder in certain scenarios. Furthermore, these results illustrate that the proposed hybrid precoding schemes have superior spectral efficiency performance while requiring lower (or at most comparable) channel feedback overhead in comparison with the prior art

Geringer RF-Komplexität Massive MIMO Systemen: Antennenselektion und Hybrid Analog-Digital Strahlformung

Wireless data traffic has been increased dramatically in the last decades, and will continue to increase in the future. As a consequence, the infrastructure of wireless communication systems needs to advance on the data capacity. Massive Multiple-Input Multiple-Output (MIMO) is a promising candidate technology to meet the demand. By scaling up the conventional MIMO by orders of magnitude number of \emph{active} antennas, a massive MIMO system can harvest considerable channel degrees of freedom to increase the spectral efficiency. However, increasing the number of \emph{active} antennas needs to increase both the numbers of Radio Frequency (RF) transceivers and antenna elements \emph{at the same rate}, which will increase the RF complexity and cost dramatically. It is known that the complexity and cost of antenna elements are usually much lower than that of RF transceivers, which motivates us to scale up MIMO by a lower increasing rate of the number of RF transceivers than that of antenna elements, resulting in so-called low RF-complexity massive MIMO systems. In this thesis, we study two types of low RF-complexity massive MIMO systems, i.e., massive MIMO antenna selection systems and massive MIMO hybrid analog-digital beamforming systems. Both systems use specific RF networks to bridge a massive number of antennas and a small number of RF transceivers, leading to signal dimension reduction from antennas to RF transceivers. The RF network used in antenna selection is referred to as RF switching network; while the RF network used in hybrid beamforming is referred to as Phase Shifting Network (PSN). Both RF networks have two types of architectures, i.e., full-array architecture and sub-array architecture. The latter has lower insertion loss, lower complexity and better scalability than the former, but at the price of performance degradation caused by connection constraint, which will be studied for both low RF-complexity systems in this thesis. In addition, a low RF-complexity PSN for the hybrid analog-digital beamforming system needs also to be studied to replace the conventional high-complexity-and-cost phase-shifter-based PSN. In the antenna selection system, the upper bounds on the channel capacity using asymptotic theory on order statistics are derived at the large-scale limit. The optimal antenna selection algorithms are also developed, which are based on Branch And Bound (BAB) search algorithm. Through the theoretical and algorithm studies, it is found that the sub-array antenna selection has close performance to the full-array antenna selection. In the hybrid beamforming system, we propose to use Rotman lens as PSN, which is of lower complexity and cost than the conventional phase-shifter-based PSN. Two beam selection algorithms, i.e., sub-optimal greedy search and optimal BAB search, are also proposed. In addition, the Rotman lenses are designed, fabricated and measured. The measurement results together with the beam selection algorithms are used to perform Monte Carlo simulation. Simulation results show that the proposed Rotman-lens-based system with the sub-array architecture suffers noticeable performance degradation compared to the system with the full-array architecture when ideal Rotman lenses are used. But when practical non-ideal Rotman lens are used, the former outperforms the latter when the number of antennas is large enough. Most interestingly, with non-ideal hardware, the sub-array Rotman-lens-based system has close performance to the sub-array phase-shifter-based system, and also exhibits a wideband capability. To prove the advantage of the low RF-complexity massive MIMO, two testbeds are built up for the antenna selection and hybrid beamforming systems, respectively. The measurement results show the low RF-complexity massive MIMO systems have superior performance over the small-scale MIMO systems under the condition of the same number of RF transceivers. The results in this thesis show that the low RF-complexity massive MIMO systems proposed in this thesis are feasible in technology and promising in performance, validating its potential usage for the future 5G wireless communication systems.Der drahtlose Datenverkehr ist in den letzten Jahrzehnten dramatisch gestiegen und wird auch in Zukunft weiter zunehmen. Infolgedessen muss die Datenkapazität der drahtlosen Infrastruktur erhöht werden. Mehrantennen Systeme mit einer sehr großen Anzahl an Antennen (engl. Massive Multiple-Input Multiple-Output (MIMO)) sind vielversprechende Technologiekandidaten, um diese Nachfrage zu erfüllen. Durch die Hochskalierung der Antennenanzahl eines konventionellen MIMO um mehrere Größenordnungen kann ein Massive MIMO-System erhebliche Kanalfreiheitsgrade erlangen, um die spektrale Effizienz zu verbessern. Allerdings muss mit der Anzahl der \emph{aktiven} Antennen sowohl die Anzahl der Hochfrequenz (engl. Radio Frequency (RF)) Transceiver als auch die der Antennenelemente \emph{im gleichen Maße} vergrössert werden, was die RF-Komplexität und Kosten dramatisch erhöht. Dabei ist bekannt, dass die Komplexität und die Kosten von Antennenelementen in der Regel viel niedriger sind als die von RF-Transceivern. Dies führt uns dazu dass wir das MIMO-System um eine im Verhältnis zur Antennenzahl geringere Anzahl von RF-Transceivern erweitern wollen, den so genannten Massive MIMO-Systemen mit geringer RF-Komplexität. In dieser Arbeit untersuchen wir zwei Arten von Massive MIMO-Systemen mit geringer RF-Komplexität, nämlich Massive MIMO-Antennenselektionssysteme und Massive MIMO-Hybrid-Analog-Digital-Strahlformungssysteme. Beide Systeme verwenden spezielle RF-Netzwerke, um eine größere Anzahl von Antennen von einer kleineren Anzahl von RF-Transceivern zu versorgen, was zu einer Signalraumreduktion von den Antennen zu den RF-Transceivern führt. Das bei der Antennenselektions verwendete RF-Netzwerk wird als RF-Koppelfeld bezeichnet, während das RF-Netzwerk, das bei der Hybrid-Strahlformung verwendet wird, als Phasenverschiebungsnetzwerk (engl. Phase Shifting Network, PSN) bezeichnet wird. Beide RF-Netzwerke können als Voll-Array-Architektur oder als Sub-Array-Architektur realisiert werden. Letztere hat eine geringere Einfügedämpfung, eine geringere Komplexität und eine bessere Skalierbarkeit als die erstere, aber zum Preis der Leistungsverschlechterung, die durch eine eingeschränkung Anzahl von Antennen-Transceiver-Verbindungen verursacht wird. Die vorliegende Arbeit untersucht dies für beide Systeme mit niedriger RF-Komplexität. Darüber hinaus wird auch ein PSN mit niedriger RF-Komplexität für das Hybride-Analog-Digital- Strahlformungssystem untersucht, das das herkömmliche hochkomplexe und kostenintensive PSN ersetzen soll. Im Antennenselektionssystem werden die Obergrenzen der Kanalkapazität unter Verwendung der Asymptoten Theorie der Ordnungsstatistik im Grenzverhalten abgeleitet. Die optimalen Antennenselektions-Algorithmen, die auf dem Branch and Bound (BAB) Suchalgorithmus basieren, werden ebenfalls entwickelt. Die theoretischen und algorithmischen Untersuchungen zeigen, dass die Leistung der Sub-Array-Antennenauswahl dicht bei der der Voll-Array-Antennenselektions liegt. Im Hybrid-Strahlformungssystem schlagen wir vor, eine Rotman-Linse als PSN zu verwenden, die von geringerer Komplexität und Kosten ist als das herkömmliche auf Phasenverschiebung basierende PSN. Es werden zwei Strahlauswahlalgorithmen vorgeschlagen, eine suboptimale Greedy-Suche und eine optimale BAB-Suche. Darüber hinaus wird die Rotman-Linse entworfen, gefertigt und vermessen. Die Messergebnisse werden zusammen mit den Strahlselektionsalgorithmen zur Durchführung einer Monte-Carlo-Simulation verwendet. Simulationsergebnisse zeigen, dass das vorgeschlagene Rotman-Linsen-basierte System mit der Sub-Array-Architektur eine spürbare Leistungsverschlechterung im Vergleich zum System mit der Full-Array-Architektur erleidet, wenn ideale Rotman-Linsen verwendet werden. Aber wenn reale nicht-ideale Rotman-Linsen verwendet werden, übertrifft erstere die zweite, wenn die Anzahl der Antennen groß genug ist. Noch interessanter, mit nicht-idealer Hardware, zeigt das Sub-Array Rotman-Linsen-basierte System in etwa die gleiche Leistung wie das Sub-Array Phasenschieber-basierte System und weist auch Breitbandfähigkeiten auf. Um den Vorteil der Massive MIMO-Systeme mit geringer RF-Komplexität zu beweisen, werden zwei Testumgebungen für die Antennenauswahl- und Hybrid-Strahlformungssysteme aufgebaut. Die Messergebnisse zeigen, dass, unter der Bedingung einer gleichen Anzahl von RF-Transceivern, die Massive MIMO-Systeme mit geringer RF-Komplexität in der Leistung den normalen MIMO-Systemen überlegen sind. Die Ergebnisse meiner Arbeit zeigen, dass die von mir vorgeschlagenen Massive MIMO-Systeme mit geringer RF-Komplexität technisch machbar und vielversprechend in der Leistung sind und bestätigen damit deren potentielle Nutzung für die zukünftigen 5G-Funkkommunikationssysteme

On the feasibility and applications of in-band full-duplex radios for future wireless networks

Due to the continuous increase of the demands for the wireless network’s capacity, in-band full-duplex (IBFD) has recently become a key research topic due to its potential to double spectral efficiency, reduce latency, enhance emerging applications, etc., by transmitting and receiving simultaneously over the same channel. Meanwhile, many studies in the literature experimentally demonstrated the feasibility of IBFD radios, which leads to the belief that it is possible to introduce IBFD in the standard of the next-generation networks. Therefore, in this thesis, we timely study the feasibility of IBFD and investigate its advantages for emerging applications in future networks. In the first part, we investigate the interference suppression methods to maximize the IBFD gain by minimizing the effects of self-interference (SI) and co-channel interference (CCI). To this end, we first study a 3-step self-interference cancellation (SIC) scheme. We focus on the time domain-based analog canceller and nonlinear digital canceller, explaining their rationale, demonstrating their effectiveness, and finding the optimal design by minimizing the residual effects. To break the limitation of conventional electrical radio frequency (RF) cancellers, we study the photonic-assisted canceller (PAC) and propose a new design, namely a fiber array-based canceller. We propose a new low-complexity tuning algorithm for the PAC. The effectiveness of the proposed fiber array canceller is demonstrated via simulations. Furthermore, we construct a prototype of the fiber array canceller with two taps and carry out experiments in real-world environments. Results show that the 3-step cancellation scheme can bring the SI close to the receiver's noise floor. Then, we consider the multiple-input multiple-output (MIMO) scenarios, proposing to employ hybrid RF-digital beamforming to reduce the implementation cost and studying its effects on the SIC design. Additionally, we propose a user allocation algorithm to reduce the CCI from the physical layer. A heterogeneous industrial Internet of Things (IIoT) scenario is considered, while the proposed algorithm can be generalized by modifying the parameters to fit any other network. In the second part, we study the beamforming schemes for IBFD multi-cell multi-user (IBFD-MCMU) networks. The transceiver hardware impairments (HWIs) and channel uncertainty are considered for robustness. We first enhance zero-forcing (ZF) and maximum ratio transmission and combining (MRTC) beamforming to be compatible with IBFD-MCMU networks in the presence of multi-antenna users. Then, we study beamforming for SIC, which is challenging for MCMU networks due to the limited antennas but complex interference. We propose a minimum mean-squared error (MMSE)-based scheme to enhance the SIC performance while minimizing its effects on the sum rate. Furthermore, we investigate a robust joint power allocation and beamforming (JPABF) scheme, which approaches the performance of existing optimal designs with reduced complexity. Their performance is evaluated and compared through 3GPP-based simulations. In the third part, we investigate the advantages of applying IBFD radios for physical layer security (PLS). We focus on a channel frequency response (CFR)-based secret key generation (SKG) scheme in MIMO systems. We formulate the intrinsic imperfections of IBFD radios (e.g., SIC overheads and noise due to imperfect SIC) and derive their effects on the probing errors. Then we derive closed-form expressions for the secret key capacity (SKC) of the SKG scheme in the presence of a passive eavesdropper. We analyze the asymptotic behavior of the SKC in the high-SNR regime and reveal the fundamental limits for IBFD and half-duplex (HD) radios. Based on the asymptotic SKC, numerical results illustrate that effective analog self-interference cancellation (ASIC) is the basis for IBFD to gain benefits over HD. Additionally, we investigate essential processing for the CFR-based SKG scheme and verify its effectiveness via simulations and the National Institute of Standards and Technology (NIST) test. In the fourth part, we consider a typical application of IBFD radios: integrated sensing and communication (ISAC). To provide reliable services in high-mobility scenarios, we introduce orthogonal time frequency space (OTFS) modulation and develop a novel framework for OTFS-ISAC. We give the channel representation in different domains and reveal the limitations and disadvantages of existing ISAC frameworks for OTFS waveforms and propose a novel radar sensing method, including a conventional MUSIC algorithm for angle estimation and a delay-time domain-based range and velocity estimator. Additionally, we study the communication design based on the estimated radar sensing parameters. To enable reliable IBFD radios in high-mobility scenarios, a SIC scheme compatible with OTFS and rapidly-changing channels is proposed, which is lacking in the literature. Numerical results demonstrate that the proposed ISAC waveform and associated estimation algorithm can provide both reliable communications and accurate radar sensing with reduced latency, improved spectral efficiency, etc

Antenna Systems

This book offers an up-to-date and comprehensive review of modern antenna systems and their applications in the fields of contemporary wireless systems. It constitutes a useful resource of new material, including stochastic versus ray tracing wireless channel modeling for 5G and V2X applications and implantable devices. Chapters discuss modern metalens antennas in microwaves, terahertz, and optical domain. Moreover, the book presents new material on antenna arrays for 5G massive MIMO beamforming. Finally, it discusses new methods, devices, and technologies to enhance the performance of antenna systems

Ergodic energy efficiency of mmWave system considering insertion loss under dynamic subarray architecture

Energy efficiency (EE) performance of millimeter-wave (mmWave) large-array systems attracts a lot of attention. And insertion loss is an inherent characteristic of hybrid precoding systems, which greatly reduces the system performance. EE analysis considering the insertion loss based on the dynamic array architecture is still an open issue. This paper researches the ergodic EE of mmWave hybrid pre-coding system with the insertion loss, based on the adaptive overlapped subarray (OSA) architecture. The ergodic EE is a more valuable indicator than the instantaneous EE for the system under dynamic architecture. However, it is difficult to directly calculate the precise ergodic EE due to the intractable relationship between EE and the channel matrix. Instead, we simplify the precise ergodic EE to get a lower bound, and analyze the ergodic EE performance based upon the lower bound. By this way, we analyze the ergodic EE performance of two typical hybrid pre-coding schemes taking the dynamic architectures. Simulation results verify the effectiveness of analyses

Abstracts on Radio Direction Finding (1899 - 1995)

The files on this record represent the various databases that originally composed the CD-ROM issue of "Abstracts on Radio Direction Finding" database, which is now part of the Dudley Knox Library's Abstracts and Selected Full Text Documents on Radio Direction Finding (1899 - 1995) Collection. (See Calhoun record https://calhoun.nps.edu/handle/10945/57364 for further information on this collection and the bibliography). Due to issues of technological obsolescence preventing current and future audiences from accessing the bibliography, DKL exported and converted into the three files on this record the various databases contained in the CD-ROM. The contents of these files are: 1) RDFA_CompleteBibliography_xls.zip [RDFA_CompleteBibliography.xls: Metadata for the complete bibliography, in Excel 97-2003 Workbook format; RDFA_Glossary.xls: Glossary of terms, in Excel 97-2003 Workbookformat; RDFA_Biographies.xls: Biographies of leading figures, in Excel 97-2003 Workbook format]; 2) RDFA_CompleteBibliography_csv.zip [RDFA_CompleteBibliography.TXT: Metadata for the complete bibliography, in CSV format; RDFA_Glossary.TXT: Glossary of terms, in CSV format; RDFA_Biographies.TXT: Biographies of leading figures, in CSV format]; 3) RDFA_CompleteBibliography.pdf: A human readable display of the bibliographic data, as a means of double-checking any possible deviations due to conversion