Frequency Division Duplex Systems Research Articles

A Novel Two-Timescale Limited Feedback Hybrid Beamforming/Combining Design for Millimeter Wave Systems

Hybrid beamforming offers a low hardware complexity for millimeter wave massive multiple-input multiple-output systems, which is divided among the analog radio frequency precoding and digital baseband precoding. In order to provide channel state information for the base station, channel feedback is essential, especially in frequency division duplexing systems. However, in large antenna systems, the size of channel matrix is huge, and the overhead of feedback complete channel is not acceptable. To reduce the feedback overhead for hybrid beamforming, leveraging the property that the millimeter wave path angles of departure vary more slowly than the path gains, we propose a two-timescale hybrid beamforming/combining algorithm for downlink multi-streams millimeter wave systems. We analyze the performance of the proposed algorithm with perfect channel state information, and the analytical and simulation results show that proposed algorithm can achieve the same performance of full digital singular value decomposition algorithm. We also analyze the rate gap between the proposed algorithm with perfect channel state information and limited feedback. The rate gap caused by quantization of radio frequency and baseband precoder codebooks are decoupled, and the quantization error is analyzed. At last, we provide a closed-form expression of relationship between feedback bits and rate gap.

Adaptive Cancellation of Digital Power Amplifier Receive Band Noise for FDD Transceivers

In frequency division duplex systems, spurious emission from transmitter (TX) can fall into receive band and lead to significant receiver desensitization. In this paper, a DSP-based solution that relies on a linear auxiliary receiver to cancel receive band noise (RxBN) from the received signal is demonstrated. This technique allows reduction of duplexer rejection requirements in the receiver band, and associated reduction of insertion loss in the TX band, thus resulting in high-power amplifier (PA) efficiency and small duplexer footprint. The PA architectures that inherently have high RxBN (such as envelope tracking and the digitally modulated PAs) can substantially benefit from this technique. Experimental results based on off-the-shelf system implementation are demonstrated using a digital PA, and more than 22 dB cancellation is achieved to reduce RxBN below thermal noise floor at 836 MHz with 45 MHz duplex spacing.

UL-CSI Data Driven Deep Learning for Predicting DL-CSI in Cellular FDD Systems

Frequency division duplex (FDD) systems dominate current cellular networks due to its advantages of low latency and strong anti-interference ability. However, the computation and the feedback overheads for predicting the downlink channel state information (DL-CSI) are the major bottlenecks to further improve the cellular FDD systems performance. To deal with these problems, in this paper, a convolutional long short-term memory network (ConvLSTM-net)-based deep learning method is proposed for predicting the DL-CSI from the uplink channel state information (UL-CSI) directly. In detail, our proposed ConvLSTM-net consists of two modules: one is the feature extraction module that learns spatial and temporal correlations between the DL-CSI and the UL-CSI, and the other one is the prediction module that maps the extracted features to the reconstructions of the DL-CSI. To evaluate the outperformance of the ConvLSTM-net, a long short-term memory network (LSTM-net) and a convolutional neural networks (CNN)-based schemes are simulated for comparisons. The simulation experiments consist of two parts. One part is that the hyper parameters of the proposed ConvLSTM-net are analyzed to explore their effects on the prediction performance. Another part is that experiments are conducted in the time domain and frequency domain, respectively, for selecting a more proper domain to predict the DL-CSI accurately. From the experiment results above, it can be verified that the proposed ConvLSTM-net with proper hyper parameters outperforms the compared schemes at predicting DL-CSI according to UL-CSI in the cellular FDD systems, especially in the time domain.

Constructing Reciprocal Channel Coefficients for Secret Key Generation in FDD Systems

Physical layer-based key generation encounters the reciprocity bottleneck when applied in frequency-division duplexing (FDD) systems. This letter constructs the reciprocal channel characteristics of the uplink and downlink transmissions for key generation in FDD systems. The frequency dependence of propagation characteristics in both large-scale fading and small-scale fading is investigated. A general channel model is then established by considering frequency impact. A reciprocal channel construction framework is finally created. Numerical results demonstrate that our algorithm can construct bidirectional channel coefficients with high correlation and thus enable key generation technology to be used in FDD systems.

Channel Feedback Codebook Design for Millimeter-Wave Massive MIMO Systems Relying on Lens Antenna Array

The recently proposed millimeter-wave (mmWave) massive multiple-input multiple-output (MIMO) system relying on a lens antenna array (LAA) significantly reduces the number of radio frequency chains using beam selection. A high data rate can be achieved based on the reduced-dimensional equivalent channel after beam selection. In frequency division duplexing systems, the equivalent channel has to be fed back to the base station (BS) via a feedback channel based on a codebook. However, no dedicated codebook has been proposed for LAA-aided mmWave systems. To fill this gap, in this letter, we propose a reduced-dimensional subspace codebook (RDSC) for such systems. Specifically, under the recently proposed concept of angle coherence time , we first generate the large-dimensional vectors in the channel subspace , which is determined by the angles-of-departure of the dominant paths. Then, based on these vectors in the channel subspace, we create the RDSC by considering both the lens and the beam selector. Finally, the equivalent channel is quantized using the proposed RDSC and fed back to the BS. Finally, we carry out mathematical performance analysis of the proposed RDSC and show that its feedback overhead is rendered proportional to the relatively small number of dominant paths per user. The analytical results are verified by our simulations.

A Six-Port Transceiver for Frequency-Division Duplex Systems

In this letter, a six-port transceiver for frequency-division duplex (FDD) systems is proposed and experimentally demonstrated. The proposed transceiver that consists of a single six-port correlator and four Schottky diodes can realize both modulation and demodulation simultaneously at different frequencies. To verify the proposed architecture, the six-port transceiver system prototypes are developed, and modulation and demodulation performances are evaluated by using quadrature amplitude modulation signals at 2.9 and 2.68 GHz, respectively. Moreover, the heterodyne demodulation for a six-port transceiver is proposed to mitigate the interferences from baseband modulation signals. The error vector magnitudes of FDD systems based on the proposed transceiver are found below 2%.

A secret key establishment in frequency division duplex communication systems under active attacker

Most of the current research on generating a secret key from wireless fading channels relies on the channel reciprocity feature of the time division duplex link between legitimate entities so that they can acquire related information from the joint wireless connection. This paper investigates the challenge of generating a shared secret key in frequency division duplex communication systems, in which there is no reciprocity between the two nodes, in the presence of an active opponent. We suggest a key generation algorithm that depends on the product of two fading coefficients. We additionally look at the effects of an interfering adversary on the suggested key establishment scheme and solve the problem of evaluating the key rate for a scheme depending on virtual channel gain. We illustrate an adversary model using an optimal attacking strategy to minimize the rate of generating a shared secret key for our suggested algorithm. Additionally, we identify the suitable channel conditions for the non‐zero rate in the existence of an interfering adversary using simulation results.

Block Bayesian matching pursuit based channel estimation for FDD massive MIMO system

Massive multi-input multi-output (MIMO) has been recognized as a key technology for 5G communication system due to the high array gain and spectral efficiency. To redeem the merits, the base station (BS) requires the accurate channel state information (CSI), which consumes large amount of pilot overhead for downlink CSI acquisition in frequency division duplex system. To address this issue, a block Bayesian matching pursuit (BBMP) based channel estimation approach is proposed, which fully exploits the common support of channels from multiple antennas at the BS. Specifically, the channel estimation problem is formulated as the block sparse recovery problem, where the prior probability for block support set is accordingly derived. Then, based on the prior knowledge and equivalent sensing matrix, a selection metric is defined to select the block index into the dominant support by exploiting the maximum likelihood criterion. Furthermore, by utilizing a matching pursuit based approach, the update criterion is derived for selection metric when the dominant support set augments with the iteration. Simulation results demonstrate that the proposed BBMP algorithm is capable to significantly reduce the pilot overhead for channel estimation and robust to the channel sparsity information.

Frequency selective digital predistortion for harmonic rejection

ABSTRACTIn recent wireless communications, spectrally flexible transmissions such as carrier aggregation and cognitive radio pose severe challenges for the high-efficient radio-frequency power amplifier (PA) design. The non-linear characteristics of PAs may yield substantial unwanted emissions that can violate the emission limits, thus interfere with other communication systems within the frequency vicinity. Furthermore, in frequency-division duplexing systems, if the unwanted emissions happen to fall into the intended receiver band, it may cause severe receiver desensitisation. In this paper, we present a novel digital predistortion (DPD) technique based on a frequency selective architecture, which is aimed at reducing the unwanted harmonic emissions at any pre-specified frequency and linearising the fundamental signal at the same time. The method can simplify the predistortion structure compared with the whole spurious suppression DPD method and thus reduce the computational complexity of the predistortion process. Furthermore, the identification of the DPD coefficients is based on a breeding particle swarm optimisation algorithm, which can enhance the calculation flexibility as well accelerate the convergence speed compared with traditional gradient methods. Both simulation and measurement results demonstrate sufficient spur suppression at the target frequency.

Stochastic Geometry Analysis of Coordinated Beamforming Small Cell Networks With CSI Delay

This letter characterizes the performance of coordinated beamforming (CBF) in frequency division duplex systems with user-centric clustering in the presence of channel state information (CSI) delay, which is modeled by Gauss–Markov auto-regressive model. A downlink model based on stochastic geometry is put forth to the analysis of statistical performance. Using the tools of stochastic geometry, the approximate expression for the average data rate of users is derived in terms of relevant system parameters. The tightness of the approximate expression is verified by Monte Carlo simulations. The approximate expression can be used to determine the optimal coordinated range. We further investigate the impact of CSI delay on the performance of CBF systems.

Improving secret key generation for wireless communications in FDD mode

SummaryMost recent research on channel‐based key generation oriented to time division duplex system because the channel reciprocity feature is applied directly for secret key generation. Most of commercial cellular systems depend on frequency division duplex (FDD) systems. In this paper, we investigate the impact of uplink and downlink of FDD systems for the generation of shared secret keys between two parties in the presents of passive eavesdropper. In addition, we are considering improving the rate of the secret key for wireless communication in FDD mode. The main idea is to use the fading coefficient of the channels between the relay and other parties as an additional random common source for the secret key generation. Also, explore the using of channel estimation techniques to reduce the channel training sequence and study its effect on the generation of shared key for wireless communications in FDD mode. We derive the upper bound of the generated shared key rate for four scenarios and give numerical examples to reveal the performance of our suggested improvement approaches.

FDD-RT: A Simple CSI Acquisition Technique via Channel Reciprocity for FDD Massive MIMO Downlink

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.

User-Centric Virtual Sectorization for Millimeter-Wave Massive MIMO Downlink

The high training cost of the massive multiple-input multiple-output (MIMO) systems motivates the use of hybrid digital/analog (HDA) beamforming structures. This paper considers the joint design of analog beamformers when both link ends of a millimeter (mm)-wave massive MIMO system are equipped with such HDA structures. We aim to maximize the multi-user MIMO net average throughput of the downlink in a frequency division duplex system. To achieve this, we develop an optimization framework, namely, user-centric virtual sectorization (UCVS), to explore the tradeoff of training overhead, beamforming gain, and spatial multiplexing gain. In the UCVS, both the channel-statistics-based analog beamforming design and a non-orthogonal downlink training scheme are investigated to reduce the necessary cost of instantaneous channel acquisition. By maximizing an approximate net average throughput, we devise efficient algorithms to realize the suboptimal UCVS. With generic mm-wave channel models, we demonstrate by simulations that our proposed scheme outperforms the state-of-the-art methods in various typical scenarios of mm-wave communications.

Localizing Noncooperative Receiver Through Full-Duplex Amplify-and-Forward Relay

Localizing noncooperative transmitter (Tx) and receiver (Rx) that belong to another system is important in many scenarios, e.g., interference management in cognitive radio systems and user behavior learning in ad hoc wireless networks. However, obtaining the locations of these nodes in particular in frequency-division duplex systems is challenging, since the localization network usually does not know the spectrum that the Rx uses for backward transmission. In this paper, we propose to use the full-duplex relay technique to localize a noncooperative Rx, which does not require the knowledge of the Rx’s backward transmission spectrum. In the proposed method, localization sensors alternatively act as a full-duplex amplify-and-forward relay to trigger the power control of the Tx–Rx link. Then, by detecting the power adjustment of the Tx, each localization sensor can estimate the time difference of arrival between the direct and relay signals. Finally, the Rx location can be calculated from triangulation. Simulation results show that the proposed method can effectively localize the Rx, which validates its potential for receiver-aware applications and services.

Joint Design of Analog and Digital Codebooks for Hybrid Precoding in Millimeter Wave Massive MIMO Systems

Hybrid precoding has been regarded as a promising technology for millimeter-wave (mmWave) massive multiple-input multiple-output (MIMO) systems due to the low hardware cost and power consumption. This paper focuses on digital and analog codebooks design to efficiently quantize the hybrid precoders with arbitrary-resolution analog phase shifters in frequency-division duplex systems. We formulate the codebooks design as a joint optimization problem and propose an iteration algorithm to obtain the enhanced codebooks based on dictionary learning methods. Moreover, this paper shows that the optimal precoders for all data streams exhibit a hidden joint sparsity structure caused by the limited number of scattering clusters with low angular spreads of mmWave MIMO channels. Exploiting the structure, a jointly sparse precoding is proposed as the pursuit method for the proposed codebooks design algorithm. The simulation results demonstrate that the near-optimal performance can be achieved by the joint utilization of the proposed hybrid precoding algorithm and codebooks even when the low-resolution phase shifters are used.

Calibration for Channel Reciprocity in Industrial Massive MIMO Antenna Systems

Massive multiple input multiple output (MIMO) antenna systems have received a great deal of interest due to their applicability to industrial network systems. One of the major obstacles that reducing the performance of massive MIMO system is reference signal (RS) overhead which can be increased as the number of transmitter antenna increases in frequency division duplexing (FDD) system. Using channel reciprocity in time division duplexing (TDD) system can significantly increase the RS overhead performance using channel reciprocity. However, to use the channel reciprocity, channel calibration is a significant challenge to overcome in real system design. There are various base station (BS) calibration methods that have already successfully applied to the current BS, while there are few methods for the calibration of distributed user entities (UEs) and/or industrial Internet of things (IIoT) devices. In this paper, we propose a distributed UE RF calibration method of massive MIMO systems that uses the power headroom report. The power headroom is typically reported from the UEs and/or IIoT devices to the BS periodically or aperiodically. By including additional amplitude RF impairment information in the power headroom report, we can successfully transfer the necessary information from UE to BS. The proposed scheme does not require additional feedback, and is in compliance with current standards. There are five schemes based on the kind of information transferred to BS and the way of making a calibration factor that can be multiplied to the estimated channel. Numerical analysis shows that the proposed schemes can significantly increase the spectral efficiency with little system burden, and thus can be a core technology for the realization of massive MIMO for industrial network systems.

Massive-MIMO Enabled FDD Wireless Backhaul Small-Cell Relay Networks: AF Protocol Based Designs With Low Channel Estimation and Feedback Complexity

To combat the explosive growth of mobile data traffic, massive-multi-input multi-output (MIMO)-enabled wireless backhaul small-cell (SC) network (WBSN) has been investigated in recent years. One of the key challenges for the WBSN is to reduce the backhaul processing delay. However, a large portion of current research has mostly been focused on the decode-and-forward (DF) protocol that inherently contains a large transmission latency due to complicated decoding process at each SC base station (SBS). In this paper, we investigate the amplify-and-forward (AF)-based WBSN. Unlike the DF schemes, the AF-WBSN is more attractive due to the cost effectiveness and lower computational complexity. In frequency division duplex (FDD) systems, however, such advantages come at the expense of high channel estimation complexity, because the macro-cell base station (MBS) in the AF-WBSN is required to know the global channel state information, which causes a significant feedback delay as well as overhead. The channel estimation becomes even more challenging when it comes to the massive MIMO systems where the MBS is equipped with a large excess of antennas. To tackle the problem, we propose a novel transceiver design for the FDD massive-MIMO enabled AF-WBSN whose channel estimation and feedback complexity reduce to the level of its DF counterpart with a low latency by leveraging the antenna correlation at the MBS and the mean squared error decomposition properties at the SBSs. Finally, numerical results verify the efficiency of our proposed designs.

A Codebook-Adaptive Feedback Algorithm for Cellular-Based Positioning

To ensure positioning accuracy and speed of cellular-based human position acquisition for location-based service in a smart system, channel state information between the base station (BS) and user equipment (UE) is required at the BS to acquire the location of users. In frequency division duplexing cellular systems, the most practical solution of channel state acquisition is that a downlink channel is quantized using a codebook and then fed back to the BS over the finite rate feedback channel. In this paper, an adaptive feedback algorithm based on codebook updating is proposed for cellular-based positioning. Different from traditional feedback schemes that the feedback codebook keeps constant during the transmission procedure, the codebook of the proposed algorithm is dynamically updated based on the varied channel by rearranging codewords synchronously at the BS and UE. The feedback overhead can be reduced effectively with low computation complexity during the feedback transmission. Numerical results validate the effectiveness of the proposed algorithm.

Beam-Time Block Coding With Joint User Grouping and Beamforming for FDD Massive MIMO Systems

A downlink (DL) precoding scheme that needs no DL training nor uplink (UL) feedback for massive MIMO systems operated under frequency-division duplex (FDD) is proposed, whereas most of the schemes in the literature were proposed to compress the overhead of training and feedback. Due to the above advantage, the proposed scheme is suitable for extremely low-latency applications. This scheme exploits angle reciprocity of FDD systems to enable the base station to acquire partial DL channel state information through a previous UL signaling. A joint user grouping and beamforming optimization method without DL training and UL feedback is proposed to enhance spectral efficiency and mitigate interference between multiple UEs during DL data transmission. Simulation results suggest that the proposed scheme possesses a comparable performance to a number of previous grouping-based schemes that require DL training and UL feedback.

A Beam Steering Based Hybrid Precoding for MU-MIMO mmWave Systems

We propose a hybrid precoding scheme for downlink multi-user multiple-input multiple-output (MU-MIMO) millimeter-wave (mmWave) systems. Firstly, the proposed precoder is designed by the beam steering condition and the zero-interference condition, which can be obtained with the information of angles of departure (AoDs) in frequency division duplex (FDD) systems. Then, the proposed precoder is decomposed into the radio frequency (RF) precoder and the baseband precoder without the loss of response. Also, array response vector selection algorithm is proposed to prevent the sum rate degradation in numerous users region. Simulation results show that the sum rate of the proposed hybrid precoder is higher than those of the block diagonalization (BD) based schemes in the region of more than 5 users and approaches the sum rate of the beam steering scheme without MU interference as the number of base station (BS) antennas increases.