Millimeter-Wave (mmWave) has emerged as a competitive solution to meet the high-data-rate requirements of future high speed train (HST) communications due to its abundant spectrum resources. However, existing research on actual measurements of mmWave channels for HST is relatively scarce, let alone at speed up to 500 km/h. This paper reports the world’s first mmWave HST channel measurement campaigns with a maglev train at a maximum speed of 500 km/h in the semi-closed station scenario. A large number of large-and small-scale fading characteristics are obtained and analyzed, such as path loss, shadow fading, root-mean-squared delay spread (RMS-DS), K factor, coherence bandwidth, and decorrelation distance. We propose an improved cluster-based Saleh-Valenzuela channel model which is more suitable for mmWave channel measurements. Numerical results and best fitting distribution results are obtained for seven key cluster parameters. The simulated and measured channels are compared to verify the accuracy of this improved model. Finally, the significance of the study is discussed, and the measurement and analysis results are compared with the existing measurement results in the train station scenario. The measurement results fill the gap of the 500 km/h mmWave HST measurements, and help to guide and design the future mmWave HST communication system.

Millimeter-wave (mmWave) technology becomes a candidate to meet the high-data-rate requirements of future vehicle-to-vehicle (V2V) communication systems. The obstructions of vehicles are particularly common in V2V communications. However, there remains a gap in existing works regarding mmWave V2V propagation with vehicle obstructions. This paper reports the mmWave V2V channel measurements and modeling with large and small vehicle obstructions in urban street and underground parking lot scenarios. The effect of the distance between the obstruction vehicle and the receiver (RX) on the mmWave channel characteristics is investigated. We employe the deterministic models (two-path, three-path and knife-edge diffraction models) considering the beam pattern of directional antennas to reveal the mmWave propagation mechanism, and propose a stochastic model that can be applied to both line-of-sight (LOS) and obstructed line-of-sight (OLOS) cases to fit the path loss. Channel non-stationarity and channel consistency are analyzed and compared. Small-scale fading characteristics, such as root-mean-square delay spread (RMS-DS), K factor and their cross-correlation, are studied in detail. The measurement and analysis results are of great help for mmWave V2V channel modeling, communication system design and performance evaluation for different scenarios and different obstruction vehicle types.

A reliable Vehicle-to-Vehicle (V2V) communication system is particularly important for intelligent transportation systems (ITS), and high-data-rate transmission is required for future V2V systems with the increase of vehicular sensors. In addition, an important V2V scenario, parking IoT, is ignored by researchers. In this paper, V2V 41GHz millimeter wave (mmWave) channel measurements are conducted in both underground and open parking IoTs for the first time. The received signal strength indication (RSSI) and channel impulse response (CIR) data are obtained by using the time domain measurement method based on Golay complementary sequences. Large- and small-scale fading characteristics, such as path loss, shadow fading, Root mean-square delay spread (RMS-DS) and Ricean K factor, are analyzed. The channel characteristics of underground parking IoT and open parking IoT are compared. The measurement and analysis results are useful for the design and channel modeling of mm Wave V2V systems in parking IoT scenario.

Parking lots, as one of the most significant vehicle-to-vehicle (V2V) communication scenarios, have rarely been studied for their millimeter-wave (mmWave) V2V channel characteristics. This paper presents the 41 GHz mmWave channel measurements and analysis results in open and underground parking lot scenarios for the first time. A large number of channel measurement data are obtained, including received signal strength indications (RSSIs) and channel impulse responses (CIRs) at different distances and different arrival angles for three cases. By clustering the power delay profile (PDP), cluster parameters such as cluster number, inter-cluster duration, cluster arrival rate and decay factor are obtained. The channel non-stationarity and consistency are revealed and discussed by various methods and from different perspectives. Large- and small-scale fading characteristics parameters, such as path loss, shadow fading, root-mean-square delay spread (RMS-DS), angle spread (AS), fade depth, and Ricean K factor are analyzed and discussed. The mmWave V2V channel characteristics of three cases are compared and analyzed. The measurement and modeling results fill the gaps of mmWave V2V channel measurements in open and underground parking lot scenarios and provide valuable suggestions for the design and modeling of mmWave V2V communication systems.

Train stations, as one of the most significant buildings on a high-speed railway (HSR), have been rarely studied for their millimeter-wave (mmWave) propagation characteristics. This paper presents the first 41 GHz mmWave band channel measurements on a HSR closed station at ultra-high speeds (up to 288 km/h). Multi-dimensional channel measurement data at different azimuth angles and speeds from inside to outside the station are obtained. It is found that the received signal strength indication (RSSI) experiences a significant attenuation caused by the influence of the station gate. In combination with the Saleh-Valenzuela (SV) model, an improved time delay clustering algorithm is used to cluster the power delay profile (PDP). According to the clustering results, parameters such as inter-cluster duration, cluster arrival rate, and intra-cluster delay spread are obtained. Most of the large- and small-scale fading characteristics, including path loss, shadow fading, PDP, angle spread, small-scale fading characteristic quantity, small-scale amplitude fading, and Rician K factor are investigated. The measurement and modeling results fill the gaps of channel measurements in closed HSR station scenarios and provide valuable suggestions for the design and modelling of HSR station communication systems.

Covert communication is crucial in privacy protection for users of wireless networks, and efforts have been made to improve the system throughput subject to a constraint on a warden's detection error probability. However, most existing research is based on an unclear relation between system throughput and covertness, due to the use of the Kullback-Leibler divergence. To solve this problem, in this paper, we explore the exact throughput-covertness relation by investigating the likelihood variation distance. An algorithm is established to find the minimum channel uses required for the transmission of a given amount of information and a certain covertness constraint. The rigorous proof of the convergence of the algorithm is also given. Our results show that an overly strict constraint on covertness would lead to a large sacrifice of system throughput, and it is not cost-effective to increase the number of channel uses to improve covertness if only a small amount of information is to be transmitted. These results could be very helpful for system designers in achieving a desirable tradeoff between system throughput and covertness.

Physical layer security can supplement upper-layer cryptographic algorithms and provide additional protection of the confidential information. The secrecy capacity of physical layer security can be further improved in massive MIMO systems through high-gain beamforming. However, previous research is mainly based on the plane-wave assumption. In massive MIMO systems with physically large arrays, it is possible that legitimate users are located in the Fresnel zone of the radiation field, which leads to spherical wavefronts. In this paper, we investigate physical layer security in the spherical-wave channel. A novel secure transmission scheme that is robust against cooperative eavesdropping is proposed. As shown by simulation results, the proposed scheme, which can be applied in the conventional plane-wave channel as well, can achieve distance-domain security in the spherical-wave channel, and thus is a potential candidate for location-based secure communications in the near future.

Differential spatial modulation (DSM) is a multiple input multiple output (MIMO) wireless transmission technique that achieves additional data bit transmission by utilizing antenna activation indexes. Combined with amplitude phase shift keying (APSK) constellations, the spectrum efficiency of DSM system can be further improved. However, the theoretically optimal maximum likelihood (ML) detection suffers from a high complexity that grows exponentially with the number of transmit antennas (TAs). Besides, the imperfect channel state information in fast fading channels leads to a severe deterioration of the detection performance. To address these problems, we propose a novel transmission scheme named reordered amplitude phase shift keying aided differential spatial modulation (RAPSK-DSM) and its low-complexity decision-feedback differential detection (DFDD) based detection algorithm. The proposed RAPSK-DSM scheme provides a better solution for addressing the error propagation problem and its detector utilizes the preceding channel gain vectors from previous detection results to mitigate the performance loss caused by time-selective channel fading. Furthermore, by decomposing and pre-computing the detection process, the complexity of proposed detector is effectively reduced due to the avoidance of redundant computations. Numerical analyses and simulation results show that the proposed RAPSK-DSM system is able to achieve substantial bit error rate (BER) performance improvement under fast fading channel conditions at the expense of low complexity.

An ultra-massive phased array can be deployed in high-throughput millimeter-wave (mmWave) communication systems to increase the transmission distance. However, when the signal bandwidth is large, the antenna array response changes with the frequency, causing beam squint. In this paper, we investigate the beam squint effect on a high-throughput mmWave communication system with the single-carrier frequency-domain equalization transmission scheme. Specifically, we first view analog beamforming and the physical channel as a spatial equivalent channel. The characteristics of the spatial equivalent channel are analyzed which behaves like frequency-selective fading. To eliminate the deep fading points in the spatial equivalent channel, an advanced analog beamforming method is proposed based on the Zadoff-Chu (ZC) sequence. Then, the low-complexity linear zero-forcing and minimum mean squared error equalizers are considered at the receiver. Simulation results indicate that the proposed ZC-based analog beamforming method can effectively mitigate the performance loss by the beam squint.

We study the problem of downlink beamforming training and channel estimation for millimeter wave (mmWave) OFDM systems, where a hybrid analog and digital beamforming structure is employed at the transmitter (i.e., base station) and an omni-directional antenna or an antenna array is used at the receiver (i.e., user). To efficiently probe the channel, we form multiple directional beams simultaneously at the transmitter and steer them towards different directions. The objective is to devise the beam training sequence and develop an efficient algorithm to estimate the channel. By exploiting the sparse scattering nature of mmWave channels, the above problem is formulated as one of sparse encoding and signal recovery, which involves finding a sparse sensing matrix to compress the sparse channel and an efficient channel estimation algorithm to recover the sparse channel from compressive measurements. In this article, we propose a sparse bipartite graph code-based algorithm, where a set of bipartite graphs are employed to encode the sparse channel and a simple decoding procedure that relies on the presence of a No-Multiton-graph (NM-graph) is used to reconstruct the sparse channel. Theoretical analysis shows that our proposed method can help achieve a substantial training overhead reduction. Simulations are provided to show the effectiveness of the proposed algorithm and its performance advantage over compressed sensing-based methods.

Massive multiple-input and multiple-output (MIMO), especially in the millimeter-wave (mmWave) frequency band, has been recognized as a promising technology for future wireless communications. However, most previous research in mmWave massive MIMO only uses conventional MIMO channel model without taking into account the spatial-wideband effect in mmWave massive MIMO systems, where the number of antennas is very large and the transmission bandwidth is very wide. In this paper, a novel mmWave massive MIMO channel model is introduced which embraces the spatial-wideband effect. Then, a joint parameter learning algorithm is proposed to extract different channel parameters from the received data. Furthermore, a low-complexity spatial wideband channel estimation scheme is proposed for the new channel model. Simulation results and complexity analysis show that the proposed scheme are capable of achieving a considerable reduction in complexity compared with the recently spatial-wideband channel estimation algorithm with a small performance loss. Moreover, our scheme can effectively estimate the novel channel even part of the antenna data is received.

The high mobility of future high-speed trains (up to 500 km/h) poses great challenges on the design of dynamic beamforming (BF) algorithms for millimeter-wave (mmWave) communications in high-speed rail (HSR) networks. Thanks to the linear structure of HSR cellular networks, the track of the train is almost predictable. Thus, the fixed BF, i.e., highly directional antennas with fixed pointing directions, can be employed as a low-cost solution to replace dynamic BF. However, the performance gap between dynamic BF and fixed BF should be evaluated to justify the use of fixed BF in HSR mmWave communications. In this paper, empirical studies are conducted based on the raw data obtained from extensive measurement campaigns. Two classic environments in railway traffic are considered: the traditional train station and the HSR tunnel. Analyses of the measurement results, including the received signal strength, power delay profile, root-mean-squared delay spread, and channel non-stationarity are presented. Then, based on the measured data, we generalize the widely-used close-in (CI) free-space path loss (PL) model so that the generalized model can characterize the PL in the HSR tunnel with a higher accuracy. Finally, the performance gap between perfect dynamic BF and fixed BF is evaluated based on the generalized model and the measured data. Our results show that the average throughput of dynamic BF is only 4% higher than that of fixed BF in the HSR tunnel, but 21% higher in the train station when severe beam misalignment is present.

Amplitude phase shift keying (APSK) aided differential spatial modulation (APSK-DSM) is a multiple-input-multiple-output wireless transmission technique which not only has the desirable features of differential spatial modulation (DSM) but also has a higher spectrum efficiency than DSM. However, the error propagation problem and the violation of the quasi-static channel assumption in conventional APSK-DSM design will cause significant performance loss, especially in undesirable channel conditions. Besides, the maximum-likelihood detection based on the traditional block-by-block search has a complexity that grows exponentially with the block size, which becomes intractable in systems with large transmit antenna numbers. To overcome those drawbacks, we propose a novel transmission scheme named the absolute amplitude differential phase spatial modulation (AADP-SM) in this paper. AADP-SM is able to alleviate the error propagation problem and achieve a near-coherent performance by invoking multiple previous blocks in the current detection. By taking into account the channel fading rate, AADP-SM is also more robust in fast-fading channels than APSK-DSM. A novel non-coherent detection algorithm is proposed for AADP-SM to reduce the exponential detection complexity to a polynomial order. Finally, we show through simulation that AADP-SM is tolerable to imperfect information about the channel statistics.

The acquisition of channel state information is crucial in massive multiple-input multiple-output (MIMO) systems when large scale antenna array is used. For Millimeter Wave (mmWave) wideband massive MIMO-OFDM systems, both the number of antennas and subcarriers are very large, so it is very difficult for us to get accurate channel information. In this paper, we propose a tensor-based channel estimation scheme for mmWave wideband channels. Firstly, we transform the two- dimensional mmWave wideband channel matrix into a three-dimensional tensor due to the large number of antennas and subcarriers. Secondly, by utilizing the PARAFAC decomposition of the tensor, the estimated three factor matrices can be obtained. Then, channel parameters can be extracted from the estimated factor matrices. Simulation results show that our proposed method outperforms the conventional low complexity compressed sensing based method, such as orthogonal matching pursuit (OMP) method, while maintaining the same complexity order.

With the development of demands in various applications for array signal processing, the number of antennas in the array and the signal bandwidth are increasing. Several direction-of-arrival (DOA) estimation algorithms have been proposed for wideband signal sources. However, the wideband algorithms are generally more complex compared with the narrowband algorithms, especially in massive antenna array systems. In this paper, we focus on analyzing the bias of narrowband multiple signal classification (MUSIC) algorithm to obtain an effective bandwidth scope in the case of non-zero bandwidth signal sources, which can guide the selection of wideband and narrowband DOA estimation algorithm in real applications. To end it, we describe the time-domain array spatial covariance matrix in non-zero bandwidth case and analyze the trend of its eigenvalues with the signal fractional bandwidth. And then an approximation DOA estimation error expression of the MUSIC algorithm is derived based on Taylor series expansion of the null spatial spectrum function. The simulation results show that the narrowband MUSIC algorithm will appear to two extreme cases, which are approximately unbiased and completely invalid in massive antenna array systems.

Hybrid beamforming architecture is a practical implementation in millimeter-wave (mmWave) communication systems with large-scale antenna arrays for future fifth-generation (5G) cellular networks, which offers a compromise between hardware complexity and system performance. Fully-connected and sub-connected are two popular connected structures in the hybrid beamforming architecture. However, the hardware complexity and the required number of phase shifters in the fully-connected structure is rather high when the number of RF chains increases. Sub-connected structure can effectively decrease the required number of phase shifters but at the expense of beamforming gain loss of each RF chain. In this paper, we consider an overlapped subarray structure between fully-connected and sub-connected structures and determine how many antenna elements should be connected for each RF chain. For the mmWave downlink multi-user multiple-input multiple-out (MIMO) communication, we design a two-stage hybrid beamforming algorithm based on the overlapped subarray structure. Simulation results indicate that there exists a best cost-effective overlapped subarray spacing associated with the required number of phase shifters for the sparse mmWave channel, which provide a guideline for the design of hybrid beamforming architecture.

Analog beamforming with large-scale phased arrays is an attractive technology for long-range millimeter- wave (mmWave) communication. However, the beam squint will emerge when the signal bandwidth and the number of antenna increase. In this end, we develop a digital compensation wideband analog beamforming architecture to eliminate the beam squint. Specifically, we view the array response and the analog beamforming as a frequency-selective channel, which is compensated in the digital baseband. The signal direction is estimated to design the analog beamforming vector and the digital compensation values using the incoherent signal subspace (ISS) wideband direction-of-arrival (DOA) estimation algorithm with 1-bit quantization. Finally, simulation results indicate that the proposed algorithm is valid in the large-scale antenna arrays, and the beam squint effect can be eliminated effectively by the digital compensation method.

Differential space time block coding (STBC) achieves full spatial diversity and avoids channel estimation overhead. Over highly frequency-selective channels, STBC is integrated with orthogonal frequency division multiplexing (OFDM) to achieve high performance. However, low-cost implementation of differential STBC- OFDM using direct-conversion transceivers is sensitive to In-phase/Quadrature-phase imbalance (IQI). In this paper, we quantify the performance impact of IQI at the receiver front-end on differential STBC-OFDM systems and propose a compensation algorithm to mitigate its effect. The proposed receiver IQI compensation works in an adaptive decision-directed manner without using known pilots or training sequences, which reduces the rate loss due to training overhead. Our numerical results show that our proposed compensation algorithm can effectively mitigate receive IQI in differential STBC-OFDM.

Symmetric α-stable (SαS) distribution noise is widely used to model co-channel and network interference in wireless communication systems. As robust and adaptive techniques, myriad filtering (MyF) and spherically symmetric vector MyF have been applied to suppress univariate and spherically symmetric multivariate SαS distribution noise, respectively. At a communication receiver, the received band-pass noisy signals are usually down-converted to complex baseband, and the resulted complex baseband SαS noise has been demonstrated not to be circularly symmetric. In this paper, we proposed a complex baseband MyF (CBMyF) to suppress the non- circularly symmetric complex baseband SαS noise. Besides, there are few researches with respect to the demodulation of memory modulation signals, e.g., minimum shift keying (MSK) signal, under SαS noise. Thus, based on CBMyF, we proposed coherent and non-coherent MSK demodulation algorithms under SαS noise in this paper. Furthermore, maximum likelihood (ML) MSK demodulation under SαS noise also been proposed. Simulation results show that the bit error rate (BER) performance of the proposed CBMyF based MSK demodulation can closely approach that of ML demodulation. Meanwhile, the proposed CBMyF is compared with the common used clipper, and the results validate its advantage of robustness and adaptivity.

A time-domain golay complementary sequences based frequency-dependent I/Q imbalance compensation scheme for receiver is presented. By utilizing property of golay sequences, the signal and its conjugate interference in preamble are separated by correlation and used to estimate the equivalent channel of I branch and Q branch. After that, a filter which contains the difference of those equivalent channels is estimated by Least Square Error (LSE) method and adopted to compensate the imbalance. The compensator structure is designed to fit the scheme so that the phase imbalance is not needed to estimate separately during the compensation. The provided scheme could be effectively applied in standards like 802.15.3c or 802.11ad where golay sequence is adopted as preamble of a frame so that there is no cost in frame structure. All the estimation and compensation are operated in time-domain thus no FFT operation is needed. Also, no further information about the channel is required, which ensures the imbalance distortion could be eliminated right after synchronization in the receiver before channel estimation and equalization. Thus, there is no strict on the algorithms of channel estimation and equalization. The performance of the scheme is evaluated by computer simulation and compared with existed algorithms. The results show that it has effectively eliminated the influence of the imbalance at a low complexity.

This paper addresses the application of the emerging compressive sensing (CS) technology to the detection of ultra-wideband (UWB) signals. Capitalizing on the sparseness of random UWB signals in the basis of eigen-functions, we develop a new CS dictionary called eigen- dictionary. Coupled with this eigen-dictionary, an enhanced Bayesian learning procedure is proposed to reconstruct the sparse UWB signal from a small collection of random projection measurements. Furthermore, by utilizing a common sparsity profile inherent in UWB signals, the proposed Bayesian algorithm naturally lends itself to multi-task CS for simultaneously recovering multiple UWB signals. Since the statistical inter-relationships between different CS tasks are exploited, the multi-task (MT) Bayesian CS can efficiently improve the reconstruction accuracy and thus the performance of UWB communications. Simulations based on real UWB data demonstrate the advantages of the proposed approach over its counterparts.

The ultra wideband (UWB) interference to code division multiple access (CDMA) system is analyzed. Two popular UWB modulation schemes, the time hopping pulse position modulation (TH-PPM) and time hopping pulse amplitude modulation (TH-PAM), are considered. The pulse repetition rate (PRR) of UWB impulse radio signal and the frequency band of the CDMA system play the primary roles in the BER performance of the CDMA system receiver in the presence of UWB interference. The characteristics of an aggregation of multiple UWB signals are somehow different from that of a single UWB device, especially for the TH-PPM scheme, where discrete spectral lines maybe exist in the band of CDMA system receiver. The system parameters of TH-PPM such as the modulation index and maximum shift incurred by the time hopping code determine the amplitude of the discrete spectral lines. In multiuser case of TH-PPM, sometimes one discrete spectral line in the band of CDMA system receiver should degrade the BER performance dramatically. It is observed by theoretical analysis and simulations that the interference to CDMA system receiver from single UWB device is very little in common case.