Showing papers on "MIMO-OFDM published in 2018"
20 May 2018
TL;DR: This analysis reveals that the proposed MIMO OTFS and OFDM systems have the same ergodic capacity despite the well-known fact that the former has great advantages in low-complexity receiver design for high Doppler channels.
Abstract: Orthogonal Time Frequency Space (OTFS) is a novel modulation scheme designed in the Doppler-delay domain to fully exploit time and frequency diversity of general time-varying channels. In this paper, we present a novel discrete-time analysis of OFDM-based OTFS transceiver with a concise and vectorized input-output relationship that clearly characterizes the contribution of each underlying signal processing block in such systems. When adopting cyclic prefix in the time domain, our analysis reveals that the proposed MIMO OTFS and OFDM systems have the same ergodic capacity despite the well-known fact that the former has great advantages in low-complexity receiver design for high Doppler channels. The proposed discrete-time vectorized formulation is applicable to general fast fading channels with arbitrary window functions. It also enables practical low-complexity receiver design for which such a concise formulation of the input-output relationship is of great benefits.
91 citations
TL;DR: Simulation results for the uncoded bit error rate of nonlinear MIMO-OFDM systems show that the introduced scheme outperforms conventional symbol detection methods.
Abstract: Reservoir computing (RC) is a class of neuromorphic computing approaches that deals particularly well with time-series prediction tasks. It significantly reduces the training complexity of recurrent neural networks and is also suitable for hardware implementation whereby device physics are utilized in performing data processing. In this paper, the RC concept is applied to detecting a transmitted symbol in multiple-input multiple-output orthogonal frequency division multiplexing (MIMO-OFDM) systems. Due to wireless propagation, the transmitted signal may undergo severe distortion before reaching the receiver. The nonlinear distortion introduced by the power amplifier at the transmitter may further complicate this process. Therefore, an efficient symbol detection strategy becomes critical. The conventional approach for symbol detection at the receiver requires accurate channel estimation of the underlying MIMO-OFDM system. However, in this paper, we introduce a novel symbol detection scheme where the estimation of the MIMO-OFDM channel becomes unnecessary. The introduced scheme utilizes an echo state network (ESN), which is a special class of RC. The ESN acts as a black box for system modeling purposes and can predict nonlinear dynamic systems in an efficient way. Simulation results for the uncoded bit error rate of nonlinear MIMO-OFDM systems show that the introduced scheme outperforms conventional symbol detection methods.
87 citations
TL;DR: With this system concept, the dual functions of the RadCom node will be possible in a realistic automotive scenario for vehicle-to-vehicle and vehicle- to-infrastructure communication with the aim of enhancing overall road safety by making driving a collaborative effort instead of an individual one.
Abstract: This paper presents a multiple-input multiple-output (MIMO) orthogonal frequency division multiplexing (OFDM) joint radar-communication (RadCom) system and explores its tolerance toward mutual interference. Since OFDM signals are weak toward subcarrier misalignment caused by frequency offsets, some form of interference cancellation will definitely be required for operation in real scenarios. A simple and flexible system level interference cancellation algorithm is proposed, which is to be employed when the radar estimation is no longer reliable. For the proof-of-concept verification, the MIMO RadCom node is implemented on universal software radio peripherals to take hardware imperfections and propagation losses into account. Real-time measurements are also presented to prove the 2D+velocity estimation capability as well as the effectiveness of the interference cancellation algorithm. With this system concept, the dual functions of the RadCom node will be possible in a realistic automotive scenario for vehicle-to-vehicle and vehicle-to-infrastructure communication with the aim of enhancing overall road safety by making driving a collaborative effort instead of an individual one.
80 citations
TL;DR: This study considers a mmWave MIMO-orthogonal frequency division multiplexing (OFDM) receiver with a generalized hybrid architecture in which a small number of radio frequency (RF) chains and low-resolution ADCs are employed simultaneously and proposes a computationally efficient data detection algorithm that provides a minimum mean-square error estimate on data symbols and is extended to a mixed-ADC architecture.
Abstract: Hybrid analog–digital precoding architectures and low-resolution analog-to-digital converter (ADC) receivers are two solutions to reduce hardware cost and power consumption for millimeter wave (mmWave) multiple-input multiple-output (MIMO) communication systems with large antenna arrays. In this study, we consider a mmWave MIMO-orthogonal frequency division multiplexing (OFDM) receiver with a generalized hybrid architecture in which a small number of radio frequency (RF) chains and low-resolution ADCs are employed simultaneously. Owing to the strong nonlinearity introduced by low-resolution ADCs, the task of data detection is challenging, particularly achieving a Bayesian optimal data detection. This study aims to fill this gap. By using a generalized expectation consistent signal recovery technique, we propose a computationally efficient data detection algorithm that provides a minimum mean-square error estimate on data symbols and is extended to a mixed-ADC architecture. Considering particular structure of MIMO-OFDM channel matrix, we provide a low-complexity realization in which only fast fourier transform (FFT) operation and matrix-vector multiplications are required. Furthermore, we present an analytical framework to study the theoretical performance of the detector in the large-system limit, which can precisely evaluate the performance expressions, such as mean-square error and symbol error rate. Based on this optimal detector, the potential of adding a few low-resolution RF chains and high-resolution ADCs for a mixed-ADC architecture is investigated. Simulation results confirm the accuracy of our theoretical analysis and can be used for system design rapidly. The results reveal that adding a few low-resolution RF chains to original unquantized systems can obtain significant gains.
78 citations
TL;DR: The approximate message passing with a nearest neighbor pattern learning algorithm is extended and capable of approaching the performance bound described by the state evolution based on vector AMP framework, and simulation results verify its superiority in mm-wave systems associated with a broad bandwidth.
Abstract: In millimeter wave (mm-wave) massive multiple-input multiple-output (MIMO) systems, acquiring accurate channel state information is essential for efficient beamforming (BF) and multiuser interference cancellation, which is a challenging task since a low signal-to-noise ratio is encountered before BF in large antenna arrays. The mm-wave channel exhibits a 3-D clustered structure in the virtual angle of arrival (AOA), angle of departure (AOD), and delay domain that is imposed by the effect of power leakage, angular spread, and cluster duration. We extend the approximate message passing (AMP) with a nearest neighbor pattern learning algorithm for improving the attainable channel estimation performance, which adaptively learns and exploits the clustered structure in the 3-D virtual AOA-AOD-delay domain. The proposed method is capable of approaching the performance bound described by the state evolution based on vector AMP framework, and our simulation results verify its superiority in mm-wave systems associated with a broad bandwidth.
76 citations
TL;DR: A fingerprint-based single-site localization method for massive multiple-input multiple-output (MIMO) orthogonal frequency-division multiplexing (OFDM) systems is proposed and an efficient location estimation method is developed to reduce storage overhead and matching complexity.
Abstract: Localization for mobile devices is drawing increasing interest from both industry and academia as location-based services spring up in recent years. For rich scattering environments, such as urban areas and indoor corridors, fingerprint-based localization techniques are very promising. In this paper, we propose a fingerprint-based single-site localization method for massive multiple-input multiple-output (MIMO) orthogonal frequency-division multiplexing (OFDM) systems. A new angle delay channel power matrix fingerprint is extracted from instantaneous channel state information by taking full advantage of the high resolution in the angle and delay domains for massive MIMO-OFDM systems. A new fingerprint similarity criterion is proposed to facilitate localization. Based on the new criterion, an efficient location estimation method is developed. To reduce storage overhead and matching complexity, we also propose a fingerprint compression method and a two-stage fingerprint clustering algorithm for database preprocessing. Numerical results demonstrate the desirable performance of the proposed localization method.
60 citations
TL;DR: This paper presents results on the achievable spectral efficiency and on the energy efficiency for a wireless multiple-input-multiple-output (MIMO) link operating at millimeter wave frequencies (mmWave) in a typical 5G scenario and shows that the best performance is achieved by single-carrier modulation with time-domain equalization.
Abstract: This paper presents results on the achievable spectral efficiency and on the energy efficiency for a wireless multiple-input-multiple-output (MIMO) link operating at millimeter wave frequencies (mmWave) in a typical 5G scenario. Two different single-carrier modem schemes are considered, i.e., a traditional modulation scheme with linear equalization at the receiver, and a single-carrier modulation with cyclic prefix, frequency-domain equalization and fast Fourier transform-based processing at the receiver; these two schemes are compared with a conventional MIMO orthogonal frequency division multiplexing transceiver structure. Our analysis jointly takes into account the peculiar characteristics of MIMO channels at mmWave frequencies, the use of hybrid (analog-digital) pre-coding and post-coding beamformers, the finite cardinality of the modulation structure, and the non-linear behavior of the transmitter power amplifiers. Our results show that the best performance is achieved by single-carrier modulation with time-domain equalization, which exhibits the smallest loss due to the non-linear distortion, and whose performance can be further improved by using advanced equalization schemes. Results also confirm that performance gets severely degraded when the link length exceeds 90–100 m and the transmit power falls below 0 dBW.
53 citations
TL;DR: This paper provides a comprehensive investigation on the DFT-precoded OFDM UWA communication with a multiple-input–multiple-output (MIMO) configuration, and corroborates its superiority for implementing a practical UWA Communication modem.
Abstract: The discrete Fourier transform (DFT) precoded orthogonal frequency-division multiplexing (OFDM) has been adopted as the uplink transmission technique in the long-term evolution terrestrial communication standard, for its lower peak-to-average power ratio (PAPR) and similar receiver complexity, compared with the standard OFDM. However, its application in the underwater acoustic (UWA) communications remains doubtful, mainly for the lack of systematic studies as well as sufficient experimental verifications. This paper provides a comprehensive investigation on the DFT-precoded OFDM UWA communication with a multiple-input–multiple-output (MIMO) configuration, and corroborates its superiority for implementing a practical UWA communication modem. The DFT precoding is applied on the data symbols to achieve a lower PAPR than that of the standard OFDM, and it is optional for the pilot symbols. The frequency-domain turbo equalization (FDTE) technique, especially suitable for interference-intensive scenarios, is employed on the receiver side to combat the intersymbol interference (ISI) and the multiplexing interference. Experimental results are provided to demonstrate the performance of the proposed transceiver scheme. It is shown reliable communication is achieved for the two-transducer transmission with a QPSK modulation and the one-transducer transmission with a 16QAM modulation, even without running any iteration for the FDTE. With the help of turbo iterations, a two-transducer transmission with a 16QAM modulation also achieves a satisfactory performance.
50 citations
TL;DR: A novel compressive recovery algorithm called adaptive support-aware block orthogonal matching pursuit for multiple input multiple output-OFDM systems is proposed to solve the problem of channel estimation for multiantenna systems.
Abstract: A new approach of channel estimation for multiantenna systems is put forward in this paper, which can be adopted in high-mobility situations such as high speed trains. The channel impulse response is abstracted as three domains to improve the modeling accuracy. Both the time-domain preamble and the frequency-domain pilot are adopted in the orthogonal frequency division multiplexing (OFDM) frame. First, the training in time domain is exploited to obtain the partial common support of the channel. Then, the pilot location optimized by the genetic algorithm is employed to build the framework of structured compressive sensing and recover the channel. A novel compressive recovery algorithm called adaptive support-aware block orthogonal matching pursuit for multiple input multiple output-OFDM systems is proposed to solve the problem. It is manifested in the simulation that the scheme in this paper outperforms the traditional ones in both recovery probability, mean square error, and bit error rate over the doubly selective channel with low computational complexity.
50 citations
TL;DR: A novel sparse channel estimation scheme is proposed, exploiting the sparsity in the delay domain and the high correlation in the spatial domain, and utilizing the basis expansion model (BEM) to model the time variation and the generalized-spatial BEM tomodel the spatial correlation.
Abstract: For downlink orthogonal frequency division multiplexing-based massive multiple-input-multiple-output transmission over the time-varying channel, channel estimation is very challenging due to numerous channel coefficients to be estimated. To track this problem, this paper proposes a novel sparse channel estimation scheme, exploiting the sparsity in the delay domain and the high correlation in the spatial domain. By utilizing the basis expansion model (BEM) to model the time variation and the generalized-spatial BEM to model the spatial correlation, we are able to significantly reduce the number of the coefficients to be estimated. Then, the channel estimation is formulated into a compressive sensing problem with a quasi-block-sparse matrix to be recovered. Motivated by the quasi-block sparsity, a novel quasi-block simultaneous orthogonal matching pursuit (QBSO) algorithm is developed to recover the channel, which seeks nonzero channel tap positions at the first stage and calculates the channel coefficients at the second stage. Moreover, an adaptive-QBSO algorithm is further designed to improve the recovery accuracy, where the measurement matrix is adaptively designed based on the estimated virtual angle of departure, and thus, the sparsity representation can be strengthened. We also discuss the design of pilot pattern including pilot values and positions. Simulation results are provided to validate the effectiveness of our proposed channel estimation scheme.
43 citations
TL;DR: The analysis of the design of statistical multiple-input-multiple-output orthogonal frequency division multiplexing (MIMO-OFDM) beamformers for millimeter wave (mmWave) channels suggests a design of the subcarriers that can be readily implemented in a hybrid structure.
Abstract: In this paper, we consider the design of statistical multiple-input-multiple-output orthogonal frequency division multiplexing (MIMO-OFDM) beamformers for millimeter wave (mmWave) channels. The transmitter designs the subcarrier beamformers based on the statistics of the channel, without instantaneous channel information. To overcome the radio frequency (RF) limitation in mmWave application, the subcarrier beamformers are implemented in a hybrid structure, which imposes constraints on the design of subcarrier beamformers. We analyze the unconstrained statistical subcarrier beamformers using spectral analysis of the subcarrier channels. The analysis shows that, for each subcarrier channel, the optimal statistical beamformer is approximately a linear combination of optimal statistical beamformers for some appropriately defined narrowband single-cluster subchannels. The result suggests a design of the subcarrier beamformers that can be readily implemented in a hybrid structure. Furthermore, a hybrid design for the receiver is proposed based on the concept of vector quantization. Simulations are given to show that the use of a hybrid beamforming structure incurs a minor degradation in transmission rate. With three RF chains, the performance is close to that of all digital statistical beamforming.
TL;DR: In this article, a linear precoding and decoding design problem for a bidirectional orthogonal frequency-division multiplexing communication system, between two MIMO full-duplex (FD) nodes, is addressed.
Abstract: In this paper, we address the linear precoding and decoding design problem for a bidirectional orthogonal frequency-division multiplexing communication system, between two multiple-input multiple-output (MIMO) full-duplex (FD) nodes. The effects of hardware distortion as well as the channel state information error are taken into account. In the first step, we transform the available time-domain characterization of the hardware distortions for FD MIMO transceivers to the frequency domain, via a linear Fourier transformation. As a result, the explicit impact of hardware inaccuracies on the residual self-interference and inter-carrier leakage is formulated in relation to the intended transmit/received signals. Afterwards, linear precoding and decoding designs are proposed to enhance the system performance following the minimum-mean-squared-error and sum rate maximization strategies, assuming the availability of perfect or erroneous channel state information. The proposed designs are based on the application of alternating optimization over the system parameters, leading to a necessary convergence. Numerical results indicate that the application of a distortion-aware design is essential for a system with a high hardware distortion, or for a system with a low thermal noise variance.
TL;DR: An overview of recent advances on the wideband waveforming, including massive multipath effect, optimal resource allocation, wireless power transfer and secrecy enhancement for secured communications, and compare with the corresponding counterparts of traditional MIMO beamforming are provided.
Abstract: By leveraging the natural multipath propagation of electromagnetic waves, waveforming is proposed as a promising paradigm that treats each multipath component in a wireless channel as a virtual antenna to exploit the spatial diversity. As the most commonly known waveforming technique for wideband systems, the time-reversal (TR) signal transmission produces a TR resonance by coherently combining multipath energy distributed on virtual antennas, and thus boosts the received signal strength while reducing interference. The wideband waveforming is, in many ways, similar to the multiple-input multiple-output (MIMO) beamforming, where multiple antennas are deployed to imitate a multipath transmission when the bandwidth is limited. In this paper, we provide an overview of recent advances on the wideband waveforming, including massive multipath effect, optimal resource allocation, wireless power transfer and secrecy enhancement for secured communications, and compare with the corresponding counterparts of traditional MIMO beamforming.
TL;DR: This paper introduces a method to increase the modulation bandwidth of an OFDM signal by using an additional frequency modulated continuous wave carrier to reduce the requirements for the AD/DA converters while maintaining a high unambiguous velocity range.
Abstract: The requirement of fast analog-to-digital (AD) and digital-to-analog (DA) converters is a challenge for high-resolution orthogonal frequency division multiplexing (OFDM) radars. This paper introduces a method to increase the modulation bandwidth of an OFDM signal by using an additional frequency modulated continuous wave carrier to reduce the requirements for the AD/DA converters while maintaining a high unambiguous velocity range. Multiplexing of transmit antennas with OFDM is still possible with the combined modulation. The presented approach is verified by simulations and measurements. A reduction of AD/DA converter bandwidth by factor eight is achieved.
TL;DR: Numerical results show that the theoretical analysis of spectral efficiency and EE is in good agreement with the simulation results and thus can be used as useful tools to improve EE.
Abstract: We investigate the feasibility of improving the energy efficiency (EE) of massive multiple-input multiple-output (MIMO) orthogonal frequency division multiplexing (OFDM) systems applied to a battery-limited Internet of Things (IoT) networks. Improving EE is especially important for battery limited IoT devices. We observe the uplink and downlink aspects of massive MIMO-OFDM-based IoT networks and categorize some of the effective methods to consider. As uplink aspect, we consider the uplink reference signal (RS) power control. Reducing uplink RS power could induce the battery saving of IoT devices but could cause an increase in channel estimation error. As downlink aspect, we consider the peak-to-average power ratio reduction of the OFDM signal and downlink transmitter power control. These techniques are well-known as effective EE improvement methods, but there is little work showing the actual EE gain in system perspective. In addition, we also consider the utilization of radio frequency energy transfer using unmanned aerial vehicles to extend the operating time of battery-limited IoT devices. We derive the theoretical closed-form approximations of spectral efficiency and EE when applying these methods and provide EE gains for various scenarios. Numerical results show that the theoretical analysis is in good agreement with the simulation results and thus can be used as useful tools to improve EE.
TL;DR: Computer simulation results show that the proposed AFSA scheme improves in both power consumptions and diversity gains compared with two existing schemes for UWA communication systems.
Abstract: This study investigates the application of artificial fish swarm algorithm (AFSA) in the power allocation for multiple-input and multiple-output orthogonal frequency-division multiplexing (MIMO-OFDM) relay underwater acoustic (UWA) communication systems. First, by using the singular value decomposition technique, the two-hop transmission links are converted into the virtual direct links in an single-input and single-output OFDM (SISO-OFDM) system. Then, a power allocation optimisation problem, together with the assignment of subcarriers and relay nodes, are formulated for the virtual SISO-OFDM system. Finally, the problem-solving algorithms are proposed in two parts. Computer simulation results show that the proposed AFSA scheme improves in both power consumptions and diversity gains compared with two existing schemes for UWA communication systems.
TL;DR: The parameterized prior-based SBL framework is employed to present a pilot scheme for an ill-posed OSTBC MIMO-OFDM channel estimation scenario and a novel scheme for joint approximately sparse channel estimation and symbol detection is developed.
Abstract: This paper presents sparse Bayesian learning (SBL)-based schemes for approximately sparse channel estimation in an orthogonal space-time block coded (OSTBC) multiple-input multiple-output (MIMO) orthogonal frequency-division multiplexing (OFDM) wireless system. The parameterized prior-based SBL framework is employed to present a pilot scheme for an ill-posed OSTBC MIMO-OFDM channel estimation scenario. Maximum likelihood symbol detection (MLSD) has been incorporated in the expectation-maximization framework for SBL-based channel estimation. This has led to the development of a novel scheme for joint approximately sparse channel estimation and symbol detection. The proposed scheme performs SBL-based channel estimation in the E-step followed by a modified ML decision metric-based symbol detection in the M-step. Bayesian Cramer–Rao bounds are obtained for the genie minimum mean-squared error estimators corresponding to the SBL schemes. Closed-form bit error probability expressions are derived for the MLSD in the presence of SBL-based channel estimation errors. Simulation results are presented towards the end to validate the theoretical bounds and illustrate the performance of the proposed techniques.
01 Dec 2018
TL;DR: Numerical results demonstrate that the spectral efficiency achieved by this proposed low-complexity BF scheme is very close to that achieved by the high- complexity fully digital BF scheme, especially when the average received power at the user is low.
Abstract: We propose a novel hybrid beamforming (BF) scheme for the Terahertz (THz) wireless communication system over frequency selective channels. In the system, a multi-antenna base station which employs the sub-connected architecture adopts orthogonal frequency division multiplexing to serve a multi- antenna user. By building a wideband THz channel model, we design a beamsteering codebook searching algorithm for analog BF in which the channel state information of all subcarriers in the radio frequency domain is considered. We then design the digital BF by using the regularized channel inversion method for eliminating inter-band interference at the baseband. Numerical results demonstrate that our proposed hybrid BF scheme achieves a significant spectral efficiency advantage over the existing hybrid BF scheme which adopted the zero-forcing digital beamformer. The results also demonstrate that the spectral efficiency achieved by our proposed low-complexity scheme is very close to that achieved by the high- complexity fully digital BF scheme, especially when the average received power at the user is low.
TL;DR: Using the antenna grouping based suboptimal scheme, it is shown that an SLM-based PAPR reduction scheme can be successfully applied to massive MIMO-OFDM antenna systems with significant increase of EE.
Abstract: Energy efficient massive multiple input multiple output (MIMO) orthogonal frequency division multiplexing (OFDM) antenna systems have received a great deal of attention for use in industrial network applications due to the possibility of reducing operation costs and carbon footprint. One of the difficulties in realizing high energy efficiency (EE) massive MIMO-OFDM antenna systems is the high peak-to-average power ratio (PAPR) of the signal, which seriously limits the efficiency of power amplifiers (PA). Selected mapping (SLM) is a powerful PAPR reduction scheme for OFDM related systems, however, there is implicit consensus that SLM could not be applied to massive MIMO-OFDM antenna systems due to its high computational complexity and side information (SI) burden. In this paper, we propose an SLM-based PAPR reduction scheme that can be applied to massive MIMO-OFDM antenna systems based on antenna grouping. Using the antenna grouping based suboptimal scheme, we show that an SLM-based PAPR reduction scheme can be successfully applied to massive MIMO-OFDM antenna systems with significant increase of EE. The proposed scheme has very high flexibility with various adjustable parameters, so one can easily choose the settings they desire between performance-complexity tradeoff. Numerical analysis shows that the propose scheme can increase EE by $18.69\%$ compared with the conventional system.
TL;DR: This paper introduces four novel construction methods for the nonsquare codewords, some of which include an arbitrary number of nonzero elements in each codeword column, and shows that the proposed encoding technique reduces the complexity of both the inverse Fourier transform and the detection processes.
Abstract: In this paper, we propose a simple yet powerful mapping scheme that converts any conventional square-matrix-based differential space-time coding (DSTC) into a nonsquare-matrix-based DSTC. This allows DSTC schemes to be used practically in open-loop large-scale multiple-input multiple-output scenarios. Our proposed scheme may be viewed as the differential counterpart of coherent spatial modulation (SM), of the generalized SM, of Bell Laboratories layered space-time architecture, and of subcarrier-index modulation. The fundamental impediment of the existing DSTC schemes is the excessive complexity imposed by the unitary constraint. Specifically, the transmission rate of conventional DSTC schemes decays as the number of transmit antennas increases. Our proposed scheme eliminates this impediment and thus achieves a significantly higher transmission rate. We introduce four novel construction methods for the nonsquare codewords, some of which include an arbitrary number of nonzero elements in each codeword column. Our analysis shows that the proposed encoding technique reduces the complexity of both the inverse Fourier transform and the detection processes. Our proposed scheme is shown to approach the performance of its coherent counterpart for low-mobility scenarios, where the number of transmit antennas is increased up to 256.
TL;DR: A low-complexity algorithm which exploits the block diagonal phase–only nature of the analog precoder in a partially connected structure is proposed to arrive at a hybrid precoding solution for a multi-carrier single-user system using orthogonal frequency division multiplexing (OFDM).
Abstract: Hybrid precoding, a combination of digital and analog precoding, is an alternative to traditional precoding methods in massive MIMO systems with a large number of antenna elements and has shown promising results recently. In this paper, we implement a parallel framework to make hybrid precoding competitive in fast-fading environments. A low-complexity algorithm which exploits the block diagonal phase–only nature of the analog precoder in a partially connected structure is proposed to arrive at a hybrid precoding solution for a multi-carrier single-user system using orthogonal frequency division multiplexing (OFDM). The original problem is broken down into two subproblems of finding the magnitude and the phase components which are solved independently. A per-RF chain power constraint is introduced instead of the sum power constraint over all antennas which are much more practical in real systems. An alternating version of the same algorithm is proposed for increased spectral-efficiency gains. Complexity and run-time analysis demonstrate the advantage of the proposed algorithm over existing hybrid precoding schemes for partially connected structure in an OFDM setting. The simulation results reveal certain insights about the partially connected structure and the tradeoffs that have to be made to make it workable in a real wideband system.
TL;DR: A novel perturbation-assisted scheme is developed to reduce the PAPRs of the transmitted signals by exploiting the redundant degrees-of-freedom inherent in the large-scale antenna array, and achieves substantial PAPR reduction within only tens of iterations.
Abstract: We consider the problem of peak-to-average power ratio (PAPR) reduction for orthogonal frequency-division multiplexing based large-scale multiple-input multiple-output systems. A novel perturbation-assisted scheme is developed to reduce the PAPRs of the transmitted signals by exploiting the redundant degrees-of-freedom inherent in the large-scale antenna array. Specifically, we introduce carefully devised perturbation signals to the frequency-domain precoded signals, with the aim of reducing the PAPRs of their time-domain counterpart signals. Meanwhile, the additive perturbation signal associated with each tone is constrained to lie in the null-space of its associated channel matrix, such that it does not cause any multiuser interference and out-of-band radiations. Such a problem is formulated as convex optimization problems, and two efficient algorithms, referred to as PROXINF-ADMM1 and PROXINF-ADMM2, are developed by resorting to the variable splitting and alterative direction method of multipliers techniques. Simulation results show that the proposed method has a fast convergence rate and achieves substantial PAPR reduction within only tens of iterations.
TL;DR: This work proposes a channel state information acquisition mechanism to reduce the training overhead in frequency-division duplexing (FDD) massive multiple-input multiple-output (MIMO) downlink (DL) by modifying theDL band training procedure in typical FDD system to reduce pilot overhead, where the DL band channel reciprocity is exploited in FDD-RT.
Abstract: We propose a channel state information acquisition mechanism to reduce the training overhead in frequency-division duplexing (FDD) massive multiple-input multiple-output (MIMO) downlink (DL). While the massive MIMO has demonstrated the great potentials in many aspects, the carrier multiplexing designs in massive MIMO mostly adopt time-division duplexing (TDD) system, which stems from a stereotype that the uplink/DL channel reciprocity only holds for TDD. On the other hand, FDD massive MIMO is generally considered infeasible due to the unaffordable temporal overhead for sending training symbols at base station. Our proposed FDD with reverse training (FDD-RT) modifies the DL band training procedure in typical FDD system to reduce pilot overhead, where the DL band channel reciprocity is exploited in FDD-RT. FDD-RT contributes to providing a feasible and relatively low complexity method to implement massive MIMO in FDD system. Without FDD-RT, communication operators who currently use FDD system may be enforced to change to TDD system in the future to accommodate massive MIMO, where the cost is prohibitive. The most different property of FDD-RT from other solutions is that its training overhead does not scale with the number of antennas at base station. The detail analysis/comparison of FDD-RT will be given in this paper.
TL;DR: SC-FDP can be considered as a promising transmission scheme for the downlink of the massive MIMO systems in the presence of carrier frequency offset and power amplifier non-linearities.
Abstract: In this paper, we investigate the suitability of single carrier frequency domain processing (SC-FDP) as the downlink transmission scheme in a massive multiple-input multiple-output (MIMO) system By deriving the sum-rate of the SC-FDP massive MIMO system theoretically, we show that this method obtains a sum-rate similar to that of orthogonal frequency division multiplexing (OFDM) massive MIMO We also derive the theoretical sum-rate of both SC-FDP and OFDM in a non-synchronized massive MIMO scenario and show that the rate of the former is significantly larger than that of the latter Moreover, we theoretically analyze the sum-rate of both systems in the presence of power amplifier non-linearity All the sum-rates are derived for both zero forcing and matched filter precoding schemes The results show that the effect of power amplifier non-linearity on the sum-rate of both systems is similar when the number of users is large We also compare SC-FDP with OFDM from the peak to average power ratio (PAPR) and complexity viewpoints Although the PAPR of SC-FDP signals is lower than that of OFDM signals, for MIMO systems, the difference between their PAPR decreases as we increase the number of users Thus, both techniques can have similar PAPR in massive MIMO systems The overall complexity of SC-FDP and OFDM is similar Due to the mentioned facts, SC-FDP can be considered as a promising transmission scheme for the downlink of the massive MIMO systems in the presence of carrier frequency offset and power amplifier non-linearities
01 Dec 2018
TL;DR: In this article, a machine learning based broadband hybrid precoding for mmWave massive MIMO with dynamic subarray (DS) is proposed, where the frequency-flat RF precoder for each subarray is extracted from the principle component of the optimal frequency-selective precoders for fully-digital MIMOs.
Abstract: Hybrid precoding design can be challenging for broadband millimeter-wave (mmWave) massive MIMO due to the frequency-flat analog precoder in radio frequency (RF). Prior broadband hybrid precoding work usually focuses on fully-connected array (FCA), while seldom considers the energy-efficient partially-connected subarray (PCS) including the fixed subarray (FS) and dynamic subarray (DS). Against this background, this paper proposes a machine learning based broadband hybrid precoding for mmWave massive MIMO with DS. Specifically, we first propose an optimal hybrid precoder based on principal component analysis (PCA) for the FS, whereby the frequency-flat RF precoder for each subarray is extracted from the principle component of the optimal frequency-selective precoders for fully-digital MIMO. Moreover, we extend the PCA-based hybrid precoding to DS, where a shared agglomerative hierarchical clustering (AHC) algorithm developed from machine learning is proposed to group the DS for improved spectral efficiency (SE). Finally, we investigate the energy efficiency (EE) of the proposed scheme for both passive and active antennas. Simulations have confirmed that the proposed scheme outperforms conventional schemes in both SE and EE.
TL;DR: Simulation results indicate that the accuracy of channel estimation can be effectively improved by the proposed scheme, whose performance is close to that of the non-interference situation.
Abstract: Cellular vehicle-to-everything (C-V2X) communications is regarded as a promising and feasible solution for 5G-enabled vehicular communications and networking. In this paper, we investigate the pilot design and channel estimation problem in MIMO-OFDM-based C-V2X systems with severe co-channel interference due to spectrum reusing among different V2X communication links. By using zero-correlation zone (ZCZ) sequences, we provide an interference-free pilot design scheme and a corresponding time-domain (TD) correlation-based channel estimation (TD-CCE) method. We employ the ZCZ sequences from the same family set to be designed as the TD pilot symbols and guarantee the pilot sequeneces for neighboring V2X communication links are code-division multiplexing (CDM). The co-channel pilot interference of the deisgned pilot symbols can be effectively eliminated by exploiting the provided TD-CCE method. Simulation results indicate that the accuracy of channel estimation can be effectively improved by the proposed scheme, whose performance is close to that of the non-interference situation.
TL;DR: Simulation results show that the proposed methods can approach the CRLB/BCRLB in both scenarios and achieve the same spectral efficiency as that obtained with the ideal channel in millimeter-wave communications.
Abstract: Beamforming with antenna arrays has been considered as an enabling technology in future wireless communication systems. To conduct beamforming, one has to know the angle-of-departure (AoD) or angle-of-arrival (AoA). For data detection, the receiver also has to know channel response. In this paper, we propose a new joint AoD, AoA, and channel estimation scheme for pilot-assisted multiple-input-multiple-output–orthogonal-frequency-division-multiplexing (MIMO-OFDM) systems. First, a compressive-sensing technique is employed to estimate the channel impulse response, exploiting the sparsity property of wireless channels. Then, AoA and AoD are jointly estimated for each detected path by the maximum likelihood method. The Cramer–Rao lower bound (CRLB) is also derived and a transmit beamforming scheme is proposed accordingly. In the scenario of available prior information, a maximum a posteriori estimation is proposed. The Bayesian CRLB (BCRLB) for the problem is also derived and a transmit beamforming scheme is further proposed. It turns out that only two training OFDM symbols are required for the estimation. Simulation results show that the proposed methods can approach the CRLB/BCRLB in both scenarios and achieve the same spectral efficiency as that obtained with the ideal channel in millimeter-wave communications.
TL;DR: The study demonstrates the performance of the FRFT-based UWA system is superior to that of the FFT- based system for all multipath scenarios, and for the flat fading channel, they achieve the same performance.
Abstract: In this study, the performance of multiple-input multiple-output (MIMO) systems based on the fractional Fourier transform (FRFT) and the fast Fourier transform (FFT) in underwater acoustic (UWA) communication channels is evaluated and compared for various conditions including the number of subcarriers, modulation schemes, the number of paths between the transmitter and the receiver, Doppler frequencies, and MIMO modes including diversity and multiplexing. The study demonstrates while the computational complexity of the FRFT is in the order of the FFT, the performance of the FRFT-based UWA system is superior to that of the FFT-based system for all multipath scenarios, and for the flat fading channel, they achieve the same performance.
20 May 2018
TL;DR: This paper proposes a multiuser MAC scheduling scheme for VR service in 5G MIMO-OFDM system, which can maximize the number of simultaneous VR clients while guaranteeing their 3UH quality-of-experience (QoE).
Abstract: Wireless Virtual Reality (VR) is a new-arising technology to enable the untethered connection between VR server and VR client, which needs to support simultaneously ultra-high data rate and ultra-high transfer reliability for video streaming, and also ultra-high responsive speed for motion-to-photon latency. Such three ultra-high (3UH) requirements constitute the basic characteristics of the generalized tactile internet. This paper proposes a multiuser MAC scheduling scheme for VR service in 5G MIMO-OFDM system, which can maximize the number of simultaneous VR clients while guaranteeing their 3UH quality-of-experience (QoE). Specifically, this scheme is composed of three novel functions, including video frame differentiation and delay-based weight calculation, spatial-frequency user selection based on maximum aggregate delay-capacity utility (ADCU), and link adaptation with dynamic block-error-rate (BLER) target. In addition, a low-complexity downlink MIMO user selection algorithm is developed, which can reduce the calculation amount with one order. It is demonstrated by the simulation results that the proposed scheme increases 31.6% for the maximum number of simultaneously served VR users than the traditional scheme with maximum-sum-capacity based scheduling and fixed BLER target based link adaptation.
15 Apr 2018
TL;DR: It is demonstrated how the basic scheme of MIMO OFDM can be modified to generate orthogonal channels, either for multiple transmitters of the same system or for different users to operate in an almost interference free state.
Abstract: This paper highlights the parameterization limitations of MIMO OFDM radar especially in multi-user scenarios. First the parameter dependencies are depicted and the resulting limitations are derived. Based on this it is demonstrated how the basic scheme can be modified to generate orthogonal channels, either for multiple transmitters of the same system or for different users to operate in an almost interference free state. The focus is on automotive applications for highly automated driving (HAD) that require both, high range and velocity resolution as well as fail save operation in scenarios with multiple users. Additionally, the limitations of Compressed Sensing in combination with OFDM radar to overcome some of the previous limitations are analyzed. Analytical studies as well as simulations have been done to depict the mentioned limitations.