Showing papers on "Spectral efficiency published in 2019"
TL;DR: Numerical results show that using the proposed phase shift design can achieve the maximum ergodic spectral efficiency, and a 2-bit quantizer is sufficient to ensure spectral efficiency degradation of no more than 1 bit/s/Hz.
Abstract: Large intelligent surface (LIS)-assisted wireless communications have drawn attention worldwide. With the use of low-cost LIS on building walls, signals can be reflected by the LIS and sent out along desired directions by controlling its phases, thereby providing supplementary links for wireless communication systems. In this paper, we evaluate the performance of an LIS-assisted large-scale antenna system by formulating a tight upper bound of the ergodic spectral efficiency and investigate the effect of the phase shifts on the ergodic spectral efficiency in different propagation scenarios. In particular, we propose an optimal phase shift design based on the upper bound of the ergodic spectral efficiency and statistical channel state information. Furthermore, we derive the requirement on the quantization bits of the LIS to promise an acceptable spectral efficiency degradation. Numerical results show that using the proposed phase shift design can achieve the maximum ergodic spectral efficiency, and a 2-bit quantizer is sufficient to ensure spectral efficiency degradation of no more than 1 bit/s/Hz.
717 citations
TL;DR: In this article, a novel concept of three-dimensional (3D) cellular networks, that integrate drone base stations (drone-BSs) and cellular-connected drone users (Drone-UEs), is introduced.
Abstract: In this paper, a novel concept of three-dimensional (3D) cellular networks, that integrate drone base stations (drone-BS) and cellular-connected drone users (drone-UEs), is introduced. For this new 3D cellular architecture, a novel framework for network planning for drone-BSs and latency-minimal cell association for drone-UEs is proposed. For network planning, a tractable method for drone-BSs’ deployment based on the notion of truncated octahedron shapes is proposed, which ensures full coverage for a given space with a minimum number of drone-BSs. In addition, to characterize frequency planning in such 3D wireless networks, an analytical expression for the feasible integer frequency reuse factors is derived. Subsequently, an optimal 3D cell association scheme is developed for which the drone-UEs’ latency, considering transmission, computation, and backhaul delays, is minimized. To this end, first, the spatial distribution of the drone-UEs is estimated using a kernel density estimation method, and the parameters of the estimator are obtained using a cross-validation method. Then, according to the spatial distribution of drone-UEs and the locations of drone-BSs, the latency-minimal 3D cell association for drone-UEs is derived by exploiting tools from an optimal transport theory. The simulation results show that the proposed approach reduces the latency of drone-UEs compared with the classical cell association approach that uses a signal-to-interference-plus-noise ratio (SINR) criterion. In particular, the proposed approach yields a reduction of up to 46% in the average latency compared with the SINR-based association. The results also show that the proposed latency-optimal cell association improves the spectral efficiency of a 3D wireless cellular network of drones.
388 citations
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TL;DR: Simulation results reveal that deploying large-scale IRSs in wireless systems is more efficient than increasing the antenna array size at the AP for enhancing both the spectral and the energy efficiency.
Abstract: Intelligent reflecting surfaces (IRSs) have received considerable attention from the wireless communications research community recently. In particular, as low-cost passive devices, IRSs enable the control of the wireless propagation environment, which is not possible in conventional wireless networks. To take full advantage of such IRS-assisted communication systems, both the beamformer at the access point (AP) and the phase shifts at the IRS need to be optimally designed. However, thus far, the optimal design is not well understood. In this paper, a point-to-point IRS-assisted multiple-input single-output (MISO) communication system is investigated. The beamformer at the AP and the IRS phase shifts are jointly optimized to maximize the spectral efficiency. Two efficient algorithms exploiting fixed point iteration and manifold optimization techniques, respectively, are developed for solving the resulting non-convex optimization problem. The proposed algorithms not only achieve a higher spectral efficiency but also lead to a lower computational complexity than the state-of-the-art approach. Simulation results reveal that deploying large-scale IRSs in wireless systems is more efficient than increasing the antenna array size at the AP for enhancing both the spectral and the energy efficiency.
309 citations
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TL;DR: The findings reveal that RIS-based IM, which enables high data rates with remarkably low error rates, can become a potential candidate for future wireless communication systems in the context of beyond multiple-input multiple-output (MIMO) solutions.
Abstract: Transmission through reconfigurable intelligent surfaces (RISs), which control the reflection/scattering characteristics of incident waves in a deliberate manner to enhance the signal quality at the receiver, appears as a promising candidate for future wireless communication systems. In this paper, we bring the concept of RIS-assisted communications to the realm of index modulation (IM) by proposing RIS-space shift keying (RIS-SSK) and RIS-spatial modulation (RIS-SM) schemes. These two schemes are realized through not only intelligent reflection of the incoming signals to improve the reception but also utilization of the IM principle for the indices of multiple receive antennas in a clever way to improve the spectral efficiency. Maximum energy-based suboptimal (greedy) and exhaustive search-based optimal (maximum likelihood) detectors of the proposed RIS-SSK/SM schemes are formulated and a unified framework is presented for the derivation of their theoretical average bit error probability. Extensive computer simulation results are provided to assess the potential of RIS-assisted IM schemes as well as to verify our theoretical derivations. Our findings also reveal that RIS-based IM, which enables high data rates with remarkably low error rates, can become a potential candidate for future wireless communication systems in the context of beyond multiple-input multiple-output (MIMO) solutions.
275 citations
TL;DR: A deep recurrent neural network-based algorithm is proposed to solve the energy efficient resource allocation (RA) problem for the NOMA-based heterogeneous IoT with fast convergence and low computational complexity.
Abstract: The Internet of Things (IoT) has attracted significant attentions in the fifth generation mobile networks and the smart cities. However, considering the large numbers of connectivity demands, it is vital to improve the spectrum efficiency (SE) of the IoT with an affordable power consumption. To improve the SE, the nonorthogonal multiple access (NOMA) technology is newly proposed through accommodating multiple users in the same spectrums. As a result, in this paper, an energy efficient resource allocation (RA) problem is introduced for the NOMA-based heterogeneous IoT. At first, we assume the successive interference cancelation (SIC) is imperfect for practical implementations. Then, based on the analyzing method for cognitive radio networks, we present a stepwise RA scheme for the mobile users and the IoT users with the mutual interference management. Third, we propose a deep recurrent neural network-based algorithm to solve the problem optimally and rapidly. Moreover, a priorities and rate demands-based user scheduling method is supplemented, to coordinate the access of the heterogeneous users with the limited radio resource. At last, the simulation results verify that the deep learning-based scheme is able to provide optimal RA results for the NOMA heterogeneous IoT with fast convergence and low computational complexity. Compared with the conventional orthogonal frequency division multiple access system, the NOMA system with imperfect SIC yields better performance on the SE and the scale of connectivity, at the cost of high power consumption and low energy efficiency.
236 citations
TL;DR: In this article, the authors investigated the integration of SWIPT in mmWave massive MIMO-NOMA systems, where each user can extract both information and energy from the received RF signals by using a power splitting receiver.
Abstract: Non-orthogonal multiple access (NOMA) has been recently considered in millimeter-wave (mmWave) massive MIMO systems to further enhance the spectrum efficiency In addition, simultaneous wireless information and power transfer (SWIPT) is a promising solution to maximize the energy efficiency In this paper, for the first time, we investigate the integration of SWIPT in mmWave massive MIMO-NOMA systems As mmWave massive MIMO will likely use hybrid precoding (HP) to significantly reduce the number of required radio-frequency (RF) chains without an obvious performance loss, where the fully digital precoder is decomposed into a high-dimensional analog precoder and a low-dimensional digital precoder, we propose to apply SWIPT in HP-based MIMO-NOMA systems, where each user can extract both information and energy from the received RF signals by using a power splitting receiver Specifically, the cluster-head selection algorithm is proposed to select one user for each beam at first, and then the analog precoding is designed according to the selected cluster heads for all beams After that, user grouping is performed based on the correlation of users’ equivalent channels Then, the digital precoding is designed by selecting users with the strongest equivalent channel gain in each beam Finally, the achievable sum rate is maximized by jointly optimizing power allocation for mmWave massive MIMO-NOMA and power splitting factors for SWIPT, and an iterative optimization algorithm is developed to solve the non-convex problem Simulation results show that the proposed HP-based MIMO-NOMA with SWIPT can achieve higher spectrum and energy efficiency compared with HP-based MIMO-OMA with SWIPT
190 citations
TL;DR: This article provides a detailed survey of all relevant research works, in which ML techniques have been used on UAV-based communications for improving various design and functional aspects such as channel modeling, resource management, positioning, and security.
Abstract: Unmanned aerial vehicles (UAVs) will be an integral part of the next generation wireless communication networks. Their adoption in various communication-based applications is expected to improve coverage and spectral efficiency, as compared to traditional ground-based solutions. However, this new degree of freedom that will be included in the network will also add new challenges. In this context, the machine-learning (ML) framework is expected to provide solutions for the various problems that have already been identified when UAVs are used for communication purposes. In this article, we provide a detailed survey of all relevant research works, in which ML techniques have been used on UAV-based communications for improving various design and functional aspects such as channel modeling, resource management, positioning, and security.
186 citations
TL;DR: This work derives the expressions of the outage probabilities and the ergodic rates and analyze the corresponding diversity orders and slopes for both backscatter-NOMA and SR systems and provides the numerical results to verify the theoretical analysis and demonstrate the interrelationship between the cellular networks and the IoT networks.
Abstract: Non-orthogonal multiple access (NOMA) is envisioned as a key technology to enhance the spectrum efficiency for 5G cellular networks. Meanwhile, ambient backscatter communication is a promising solution to the Internet of Things (IoT), due to its high spectrum efficiency and power efficiency. In this paper, we are interested in a symbiotic system of cellular and IoT networks and propose a backscatter-NOMA system, which incorporates a downlink NOMA system with a backscatter device (BD). In the proposed system, the base station (BS) transmits information to two cellular users according to the NOMA protocol, while a BD transmits its information over the BS signals to one cellular user using the passive radio technology. In particular, if the BS only serves the cellular user that decodes BD information, the backscatter-NOMA system turns into a symbiotic radio (SR) system. We derive the expressions of the outage probabilities and the ergodic rates and analyze the corresponding diversity orders and slopes for both backscatter-NOMA and SR systems. Finally, we provide the numerical results to verify the theoretical analysis and demonstrate the interrelationship between the cellular networks and the IoT networks.
165 citations
TL;DR: A damped three dimensional (D3D) message-passing algorithm (MPA) based on deep learning is proposed and an analogous back propagation algorithm is developed to learn the optimal parameters of the D3D-MPA.
Abstract: Energy efficiency (EE) and spectrum efficiency (SE) have received significant attentions on optimizing the network performance in cognitive radio networks. In this paper, an EE+SE tradeoff based target is considered for the primary users (PUs) and the secondary users (SUs). First of all, considering the orthogonal frequency division multiple access-based resource allocation (RA) for the underlying SUs, we formulate an objective function through minimizing a weighted sum of the secondary interference power, where the network performance of both PUs and SUs are guaranteed by the constraints on quality of service, power consumption and data rate. However, it is a NP-hard problem. In order to solve it, we propose a damped three dimensional (D3D) message-passing algorithm (MPA) based on deep learning. Specifically, a feed-forward neural network is devised and an analogous back propagation algorithm is developed to learn the optimal parameters of the D3D-MPA. To improve the computational efficiency of the allocation and the learning, a suboptimal RA scheme is deduced based on a damped two dimensional MPA. Finally, simulation results are provided to confirm the effectiveness of our proposed scheme.
161 citations
TL;DR: A dual-layer algorithm where Dinkelbach method is employed both in the inner layer to optimize the power allocation and in the outer layer to control the time switching assignment is developed and demonstrated that significant performance gain over orthogonal multiple access scheme in terms of EE can be achieved in a SWIPT-enabled NOMA system.
Abstract: The combination of simultaneous wireless information and power transfer (SWIPT) and non-orthogonal multiple access (NOMA) is a potential solution to improve spectral efficiency and energy efficiency (EE) of the upcoming fifth generation (5G) networks, especially in order to support the functionality of the Internet of things (IoT) and the massive machine-type communications (mMTC) scenarios. In this paper, we investigate joint power allocation and time switching (TS) control for EE optimization in a TS-based SWIPT NOMA system. Our aim is to optimize the EE of the system whilst satisfying the constraints on maximum transmit power budget, minimum data rate, and minimum harvested energy per terminal. The considered EE optimization problem is neither linear nor convex involving joint optimization of power allocation and time switching factors and, thus, is extremely difficult to solve directly. In order to tackle this problem, we develop a dual-layer algorithm where Dinkelbach method is employed both in the inner layer to optimize the power allocation and in the outer layer to control the time switching assignment. Furthermore, a simplified but practical special case with equal time switching factors in all terminals is considered. Numerical results validate the theoretical findings and demonstrate that significant performance gain over orthogonal multiple access scheme in terms of EE can be achieved by the proposed algorithms in a SWIPT-enabled NOMA system.
160 citations
22 Jun 2019
TL;DR: This paper considers the downlink transmit power minimization problem for a IRS- empowered non-orthogonal multiple access (NOMA) network by jointly optimizing the transmit beamformers at the BS and the phase-shift matrix at the IRS and develops a novel difference-of-convex (DC) programming algorithm to solve the resulting non- Convex quadratic programs efficiently.
Abstract: Intelligent reflecting surface (IRS) has recently been recognized as a promising technology to enhance the energy and spectrum efficiency of wireless networks by controlling the wireless medium with the configurable electromagnetic materials. In this paper, we consider the downlink transmit power minimization problem for a IRS- empowered non-orthogonal multiple access (NOMA) network by jointly optimizing the transmit beamformers at the BS and the phase-shift matrix at the IRS. However, this problem turns out to be a highly intractable non-convex bi- quadratic programming problem, for which an alternative minimization framework is proposed via solving the non- convex quadratic programs alternatively. We further develop a novel difference-of-convex (DC) programming algorithm to solve the resulting non-convex quadratic programs efficiently by lifting the quadratic programs into rank-one constrained matrix optimization problems, followed by representing the non-convex rank function as a DC function. Simulation results demonstrate the performance gains of the proposed method.
TL;DR: In this article, a unified model for NOMA, including uplink and downlink transmissions, along with the extensions tomultiple input multiple output and cooperative communication scenarios, is presented.
Abstract: Today's wireless networks allocate radio resources to users based on the orthogonal multiple access (OMA) principle. However, as the number of users increases, OMA based approaches may not meet the stringent emerging requirements including very high spectral efficiency, very low latency, and massive device connectivity. Nonorthogonal multiple access (NOMA) principle emerges as a solution to improve the spectral efficiency while allowing some degree of multiple access interference at receivers. In this tutorial style paper, we target providing a unified model for NOMA, including uplink and downlink transmissions, along with the extensions tomultiple inputmultiple output and cooperative communication scenarios. Through numerical examples, we compare the performances of OMA and NOMA networks. Implementation aspects and open issues are also detailed.
TL;DR: This paper aims to maximize the entire system energy efficiency, including the macrocell and small cells, in a NOMA HetNet via subchannel allocation and power allocation via convex relaxation and dual-decomposition techniques.
Abstract: Non-orthogonal multiple access (NOMA) has been considered as a key technology in the fifth-generation mobile communication networks due to its superior spectrum efficiency. Since the heterogeneous network has been emerged to satisfy users’ explosive data rate requirements and large connectivity of mobile Internet, implementing NOMA policy in heterogeneous networks (HetNets) has become an inevitable trend to enhance the 5G system throughput and spectrum efficiency. In this paper, we aim to maximize the entire system energy efficiency, including the macrocell and small cells, in a NOMA HetNet via subchannel allocation and power allocation. By considering the co-channel interference and cross-tier interference, the energy efficient resource allocation problem is formulated as a mixed integer nonconvex optimization problem. It is challenging to obtain the optimal solution; therefore, a suboptimal algorithm is proposed to alternatively optimize the macrocell and the small cells resource allocation. Specifically, convex relaxation and dual-decomposition techniques are exploited to optimize the subchannel allocation and power allocation. Moreover, optimal closed-form power allocation expressions are derived for small cell and macrocell user equipments by the Lagrangian approach. Simulations results show that the proposed algorithms can converge within ten iterations and can also attain higher system energy efficiency than the reference schemes.
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TL;DR: A system for serving paired power-domain non-orthogonal multiple access (NOMA) users by designing the passive beamforming weights at the RISs is conceived, and the proposed RIS-aided NOMA network has superior network performance compared to its orthogonal counterpart.
Abstract: Reconfigurable intelligent surfaces (RISs) constitute a promising performance enhancement for next-generation (NG) wireless networks in terms of enhancing both their spectrum efficiency (SE) and energy efficiency (EE). We conceive a system for serving paired power-domain non-orthogonal multiple access (NOMA) users by designing the passive beamforming weights at the RISs. In an effort to evaluate the network performance, we first derive the best-case and worst-case of new channel statistics for characterizing the effective channel gains. Then, we derive the best-case and worst-case of our closed-form expressions derived both for the outage probability and for the ergodic rate of the prioritized user. For gleaning further insights, we investigate both the diversity orders of the outage probability and the high-signal-to-noise (SNR) slopes of the ergodic rate. We also derive both the SE and EE of the proposed network. Our analytical results demonstrate that the base station (BS)-user links have almost no impact on the diversity orders attained when the number of RISs is high enough. Numerical results are provided for confirming that: i) the high-SNR slope of the RIS-aided network is one; ii) the proposed RIS-aided NOMA network has superior network performance compared to its orthogonal counterpart.
TL;DR: This work proposes a hybrid beamforming design for FD mmWave communications, where the SI is canceled by the joint design of beamformer weights at the radio-frequency and the precoder as well as combiner in the baseband, which significantly outperforms eigen-beamforming.
Abstract: Harnessing the abundant availability of spectral resources at millimeter wave (mmWave) frequencies is an attractive solution to meet the escalating data rate demands. Additionally, it has been shown that full-duplex (FD) communication has the potential of doubling the bandwidth efficiency. However, the presence of significant residual self-interference (SI), which is especially more pronounced at mmWave frequencies because of the non-linearities in the hardware components, erodes the full potential of FD in practice. Conventionally, the residual SI is canceled in the baseband using digital processing with the aid of a transmit precoder. In this work, we propose a hybrid beamforming design for FD mmWave communications, where the SI is canceled by the joint design of beamformer weights at the radio-frequency and the precoder as well as combiner in the baseband. Our proposed design preserves the dimensions of the transmit signal, while suppressing the SI. We demonstrate that our joint design is capable of reducing the SI by upto 30 dB, hence performing similarly to the interference-free FD system while being computationally efficient. Our simulation results show that the proposed design significantly outperforms eigen-beamforming.
TL;DR: In this article, a multi-beam non-orthogonal multiple access (NOMA) scheme for hybrid millimeter wave (mmWave) systems and its resource allocation is proposed.
Abstract: In this paper, we propose a multi-beam non-orthogonal multiple access (NOMA) scheme for hybrid millimeter wave (mmWave) systems and study its resource allocation. A beam splitting technique is designed to generate multiple analog beams to serve multiple NOMA users on each radio frequency chain. In contrast to the recently proposed single-beam mmWave-NOMA scheme which can only serve multiple NOMA users within the same analog beam, the proposed scheme can perform NOMA transmission for the users with an arbitrary angle-of-departure distribution. This provides a higher flexibility for applying NOMA in mmWave communications and thus can efficiently exploit the potential multi-user diversity. Then, we design a suboptimal two-stage resource allocation for maximizing the system sum-rate. In the first stage, assuming that only analog beamforming is available, a user grouping and antenna allocation algorithm is proposed to maximize the conditional system sum-rate based on the coalition formation game theory. In the second stage, with the zero-forcing digital precoder, a suboptimal solution is devised to solve a non-convex power allocation optimization problem for the maximization of the system sum-rate which takes into account the quality of service constraints. Simulation results show that our designed resource allocation can achieve a close-to-optimal performance in each stage. In addition, we demonstrate that the proposed multi-beam mmWave-NOMA scheme offers a substantial spectral efficiency improvement compared to that of the single-beam mmWave-NOMA and the mmWave orthogonal multiple access schemes.
01 Aug 2019
TL;DR: In this article, a point-to-point RIS-assisted multiple-input single-output (MISO) communication system is investigated, where the beamformer at the access point and the RIS phase shifts are jointly optimized to maximize the spectral efficiency.
Abstract: Intelligent reflecting surfaces (IRSs) have received considerable attention from the wireless communications research community recently. In particular, as low-cost passive devices, IRSs enable the control of the wireless propagation environment, which is not possible in conventional wireless networks. To take full advantage of such IRS-assisted communication systems, both the beamformer at the access point (AP) and the phase shifts at the IRS need to be optimally designed. However, thus far, the optimal design is not well understood. In this paper, a point-to-point IRS-assisted multiple-input single-output (MISO) communication system is investigated. The beamformer at the AP and the IRS phase shifts are jointly optimized to maximize the spectral efficiency. Two efficient algorithms exploiting fixed point iteration and manifold optimization techniques, respectively, are developed for solving the resulting non-convex optimization problem. The proposed algorithms not only achieve a higher spectral efficiency but also lead to a lower computational complexity than the state-of-the-art approach. Simulation results reveal that deploying large-scale IRSs in wireless systems is more efficient than increasing the antenna array size at the AP for enhancing both the spectral and the energy efficiency.
TL;DR: In this paper, a non-orthogonal multiple access (NOMA) transmission protocol that incorporates orthogonal time frequency space (OTFS) modulation is proposed, where users with different mobility profiles are grouped together for the implementation of NOMA.
Abstract: This paper considers a challenging communication scenario, in which users have heterogenous mobility profiles, e.g., some users are moving at high speeds and some users are static. A new non-orthogonal multiple-access (NOMA) transmission protocol that incorporates orthogonal time frequency space (OTFS) modulation is proposed. Thereby, users with different mobility profiles are grouped together for the implementation of NOMA. The proposed OTFS-NOMA protocol is shown to be applicable to both uplink and downlink transmission, where sophisticated transmit and receive strategies are developed to remove inter-symbol interference and harvest both multi-path and multi-user diversity. Analytical results demonstrate that both the high-mobility and the low-mobility users benefit from the application of OTFS-NOMA. In particular, the use of NOMA allows the spreading of the high-mobility users’ signals over a large amount of time-frequency resources, which enhances the OTFS resolution and improves the detection reliability. In addition, OTFS-NOMA ensures that low-mobility users have access to bandwidth resources which in conventional OTFS-orthogonal multiple access (OTFS-OMA) would be solely occupied by the high-mobility users. Thus, OTFS-NOMA improves the spectral efficiency and reduces latency.
TL;DR: The proposed mobile VR delivery framework is promising in improving spectral efficiency by maximizing average tolerant delay while meeting high transmission rate requirements and the communications-caching-computing tradeoff at both mobile VR devices and F-APs is revealed.
Abstract: The emerging virtual reality (VR) experience demands ultra-high-transmission-rate and ultra-low-latency deliveries, which is challenging for the current cellular networks. Since fog radio access networks (F-RANs) take full advantages of both edge fog computing and caching technologies and benefit different quality-of-service requirements, it is anticipated that high-quality VR experience could be well addressed in F-RANs. This paper presents an F-RAN-based mobile VR delivery framework, in which the core idea is to cache parts of the VR videos in advance and run a certain processing procedure at the edge of F-RANs. To optimize resource allocation at both mobile VR devices and fog access points (F-APs), a joint radio communication, caching and computing decision problem is formulated to maximize the average tolerant delay with meeting a given transmission rate constraint. This problem is formulated as a multiple choice multiple dimensional knapsack problem and solved with the Lagrangian dual decomposition approach. Furthermore, the optimal joint caching and computing decision is analyzed in a specific case with a closed-form expression of the average tolerant delay. The communications-caching-computing tradeoff at both mobile VR devices and F-APs is revealed, and the numerical results demonstrate that local caching and computing capabilities have significant impacts on the average tolerant delay. The proposed mobile VR delivery framework is promising in improving spectral efficiency by maximizing average tolerant delay while meeting high transmission rate requirements.
TL;DR: Two deep learning architectures are proposed, Dual net-MAG and DualNet-ABS, to significantly reduce the CSI feedback payload based on the multipath reciprocity, based on limited feedback and bi-directional reciprocal channel characteristics.
Abstract: Channel state information (CSI) feedback is important for multiple-input multiple-output (MIMO) wireless systems to achieve their capacity gain in frequency division duplex mode. For massive MIMO systems, CSI feedback may consume too much bandwidth and degrade spectrum efficiency. This letter proposes a learning-based CSI feedback framework based on limited feedback and bi-directional reciprocal channel characteristics. The massive MIMO base station exploits the available uplink CSI to help recovering the unknown downlink CSI from low rate user feedback. We propose two deep learning architectures, DualNet-MAG and DualNet-ABS, to significantly reduce the CSI feedback payload based on the multipath reciprocity. DualNet-MAG and DualNet-ABS can exploit the bi-directional correlation of the magnitude and the absolute value of real/imaginary parts of the CSI coefficients, respectively. The experimental results demonstrate that our architectures bring an obvious improvement compared with the downlink-based architecture.
TL;DR: This paper investigates the channel state information (CSI) acquisition problem for mmWave massive MIMO with hybrid analog-digital antenna architecture and an iterative analog beam acquisition approach is proposed to save system overhead and reduce beam searching complexity.
Abstract: Massive Multiple-Input Multiple-Output (MIMO) is considered as a key technology for 4G and 5G wireless communication systems to improve spectrum efficiency by supporting large number of concurrent users. In addition, for the target frequency band of 5G system, mmWave band, massive MIMO is pivotal in compensating the high pathloss. In this paper, we investigate the channel state information (CSI) acquisition problem for mmWave massive MIMO. With hybrid analog-digital antenna architecture, how to derive the analog beamforming and digital beamforming is studied. An iterative analog beam acquisition approach is proposed to save system overhead and reduce beam searching complexity. Regarding the digital beamforming, a grouping based codebook is proposed to facilitate CSI feedback. The codebook is then extended to incorporate also analog beam acquisition. Furthermore, channel reciprocity is exploited to save CSI reporting overhead and a two-stage approach is proposed to fully utilize the channel reciprocity at both mobile station and base station side and accelerate the CSI acquisition procedure.
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TL;DR: In this article, the authors considered the downlink transmit power minimization problem for a RIS-empowered non-orthogonal multiple access (NOMA) network by jointly optimizing the transmit beamformers at the BS and the phase shift matrix at the IRS.
Abstract: Intelligent reflecting surface (IRS) has recently been recognized as a promising technology to enhance the energy and spectrum efficiency of wireless networks by controlling the wireless medium with the configurable electromagnetic materials. In this paper, we consider the downlink transmit power minimization problem for a IRS-empowered non-orthogonal multiple access (NOMA) network by jointly optimizing the transmit beamformers at the BS and the phase shift matrix at the IRS. However, this problem turns out to be a highly intractable non-convex bi-quadratic programming problem, for which an alternative minimization framework is proposed via solving the non-convex quadratic programs alternatively. We further develop a novel difference-of-convex (DC) programming algorithm to solve the resulting non-convex quadratic programs efficiently by lifting the quadratic programs into rank-one constrained matrix optimization problems, followed by representing the non-convex rank function as a DC function. Simulation results demonstrate the performance gains of the proposed method.
TL;DR: In this paper, the authors proposed and demonstrated a scheme to optimize the fiber input powers for UWB transmission systems considering the signal power transition caused by the inter-band stimulated Raman scattering (SRS).
Abstract: Ultra-wideband (UWB) wavelength division multiplexed (WDM) transmission using high-order modulation formats is one of the key techniques to expand the transmission capacity per optical fiber. For UWB systems, the nonlinear interaction caused by inter-band stimulated Raman scattering (SRS) must be considered. Therefore, we have proposed and demonstrated a scheme to optimize the fiber input powers for UWB transmission systems considering the signal power transition caused by the inter-band SRS. We demonstrated a single-mode capacity of 150.3 Tb/s using the proposed power optimization scheme with 13.6-THz UWB in the S-, C-, and L-bands over 40-km transmission. Spectral efficiency of 11.05 b/s/Hz was achieved with 272-channel 50-GHz spaced WDM signals of 45-GBaud polarization division multiplexed 128 quadrature amplitude modulation.
TL;DR: In this paper, the authors examined spatial modulation techniques that can leverage the properties of densely packed configurable arrays of subarrays of nano-antennas, to increase capacity and spectral efficiency, while maintaining acceptable beamforming performance.
Abstract: The prospect of ultra-massive multiple-input multiple-output (UM-MIMO) technology to combat the distance problem at the Terahertz (THz) band is considered. It is well-known that the very large available bandwidths at THz frequencies come at the cost of severe propagation losses and power limitations, which result in very short communication distances. Recently, graphene-based plasmonic nano-antenna arrays that can accommodate hundreds of antenna elements in a few millimeters have been proposed. While such arrays enable efficient beamforming that can increase the communication range, they fail to provide sufficient spatial degrees of freedom for spatial multiplexing. In this paper, we examine spatial modulation (SM) techniques that can leverage the properties of densely packed configurable arrays of subarrays of nano-antennas, to increase capacity and spectral efficiency, while maintaining acceptable beamforming performance. Depending on the communication distance and the frequency of operation, a specific SM configuration that ensures good channel conditions is recommended. We analyze the performance of the proposed schemes theoretically and numerically in terms of symbol and bit error rates, where significant gains are observed compared to conventional SM. We demonstrate that SM at very high frequencies is a feasible paradigm, and we motivate several extensions that can make THz-band SM a future research trend.
TL;DR: A deep learning based BF design approach is proposed and a BF neural network (BFNN) is developed which can be trained to learn how to optimize the beamformer for maximizing the spectral efficiency with hardware limitation and imperfect CSI.
Abstract: Beamforming (BF) design for large-scale antenna arrays with limited radio frequency chains and the phase-shifter-based analog BF architecture, has been recognized as a key issue in millimeter wave communication systems. It becomes more challenging with imperfect channel state information (CSI). In this letter, we propose a deep learning based BF design approach and develop a BF neural network (BFNN) which can be trained to learn how to optimize the beamformer for maximizing the spectral efficiency with hardware limitation and imperfect CSI. Simulation results show that the proposed BFNN achieves significant performance improvement and strong robustness to imperfect CSI over the conventional BF algorithms.
TL;DR: A novel scheme termed layered orthogonal frequency division multiplexing with index modulation (L-OFDM-IM) to increase the spectral efficiency (SE) of OF DM-IM systems is proposed and results show that L-OFdm-IM outperforms the conventional OFDM- IM scheme.
Abstract: In this paper, we propose a novel scheme termed layered orthogonal frequency division multiplexing with index modulation (L-OFDM-IM) to increase the spectral efficiency (SE) of OFDM-IM systems. In L-OFDM-IM, all subcarriers are first divided into multiple layers, each determining the active subcarriers and their modulated symbols. The index modulation (IM) bits are carried on the indices of the active subcarriers of all layers, which are overlapped and distinguishable with different signal constellations so that the number of the IM bits is larger than that in traditional OFDM-IM. A low-complexity detection is proposed to alleviate the high burden of the optimal maximum-likelihood detection at the receiver side. A closed-form upper bound on the bit error rate, the achievable rate, and diversity order are derived to characterize the performance of L-OFDM-IM. To enhance the diversity performance of L-OFDM-IM, we further propose coordinate interleaving L-OFDM-IM (CI-L-OFDM-IM), which interleaves the real and imaginary parts of the modulated symbols over two different subchannels. Computer simulations verify the theoretical analysis, and results show that L-OFDM-IM outperforms the conventional OFDM-IM scheme. Moreover, it is also confirmed that CI-L-OFDM-IM obtains an additional diversity order in comparison with L-OFDM-IM.
TL;DR: The proposed MA method is analytically shown to be MUI free and therefore has a significantly higher sum spectral efficiency when compared to other methods proposed in literature which utilize guard bands in the DD domain to reduce MUI.
Abstract: We propose a multiple-access (MA) method in the uplink of a orthogonal time frequency space modulation-based wireless communication system where the channel has high Doppler and delay spread. Each user terminal (UT) is allocated delay-Doppler (DD) resource blocks which are spaced at equal intervals in the DD domain. This limits the corresponding time-frequency (TF) transmit signal to a sub-domain of the entire TF domain. By allocating non-overlapping portions to the TF transmit signal of different UTs, multi-user interference (MUI) is avoided. The proposed MA method is analytically shown to be MUI free and therefore has a significantly higher sum spectral efficiency when compared to other methods proposed in literature which utilize guard bands in the DD domain to reduce MUI.
TL;DR: Numerical results show that both data power control and LSFD improve the sum SE performance over single-layer decoding multi-cell Massive MIMO systems.
Abstract: Massive multiple-input–multiple-output (MIMO) systems can suffer from coherent intercell interference due to the phenomenon of pilot contamination. This paper investigates a two-layer decoding method that mitigates both coherent and non-coherent interference in multi-cell Massive MIMO. To this end, each base station (BS) first estimates the channels to intra-cell users using either minimum mean-squared error (MMSE) or element-wise MMSE estimation based on uplink pilots. The estimates are used for local decoding on each BS followed by a second decoding layer where the BSs cooperate to mitigate inter-cell interference. An uplink achievable spectral efficiency (SE) expression is computed for arbitrary two-layer decoding schemes. A closed form expression is then obtained for correlated Rayleigh fading, maximum-ratio combining, and the proposed large-scale fading decoding (LSFD) in the second layer. We also formulate a sum SE maximization problem with both the data power and LSFD vectors as optimization variables. Since this is an NP-hard problem, we develop a low-complexity algorithm based on the weighted MMSE approach to obtain a local optimum. The numerical results show that both data power control and LSFD improve the sum SE performance over single-layer decoding multi-cell Massive MIMO systems.
30 Jul 2019
TL;DR: A cell-free Massive multiple-input multiple-output (MIMO) uplink is considered, where the access points are connected to a central processing unit (CPU) through limited-capacity wireless microwave links and an iterative algorithm is proposed to alternately solve each sub-problem.
Abstract: A cell-free Massive multiple-input multiple-output (MIMO) uplink is considered, where the access points (APs) are connected to a central processing unit (CPU) through limited-capacity wireless microwave links. The quantized version of the weighted signals are available at the CPU, by exploiting the Bussgang decomposition to model the effect of quantization. A closed-form expression for spectral efficiency is derived taking into account the effects of channel estimation error and quantization distortion. The energy efficiency maximization problem is considered with per-user power, backhaul capacity and throughput requirement constraints. To solve this non-convex problem, we decouple the original problem into two sub-problems, namely, receiver filter coefficient design, and power allocation. The receiver filter coefficient design is formulated as a generalized eigenvalue problem whereas a successive convex approximation (SCA) and a heuristic sub-optimal scheme are exploited to convert the power allocation problem into a standard geometric programming (GP) problem. An iterative algorithm is proposed to alternately solve each sub-problem. Complexity analysis and convergence of the proposed schemes are investigated. Numerical results indicate the superiority of the proposed algorithms over the case of equal power allocation.
TL;DR: This work analyzes a constrained version of the Maximum Likelihood (ML) problem (a combinatorial optimization with exponential complexity) and finds the same fundamental scaling law for the number of identifiable users and provides two algorithms based on Non-Negative Least-Squares.
Abstract: In this paper, we study the problem of user activity detection and large-scale fading coefficient estimation in a random access wireless uplink with a massive MIMO base station with a large number $M$ of antennas and a large number of wireless single-antenna devices (users). We consider a block fading channel model where the $M$-dimensional channel vector of each user remains constant over a coherence block containing $L$ signal dimensions in time-frequency. In the considered setting, the number of potential users $K_\text{tot}$ is much larger than $L$ but at each time slot only $K_a<