Pilot Channel Research Articles

Artificial Noise-Aided Physical Layer Security in Underlay Cognitive Massive MIMO Systems with Pilot Contamination

In this paper, a secure communication model for cognitive multi-user massive multiple-input multiple-output (MIMO) systems with underlay spectrum sharing is investigated. A secondary (cognitive) multi-user massive MIMO system is operated by using underlay spectrum sharing within a primary (licensed) multi-user massive MIMO system. A passive multi-antenna eavesdropper is assumed to be eavesdropping upon either the primary or secondary confidential transmissions. To this end, a physical layer security strategy is provisioned for the primary and secondary transmissions via artificial noise (AN) generation at the primary base-station (PBS) and zero-forcing precoders. Specifically, the precoders are constructed by using the channel estimates with pilot contamination. In order to degrade the interception of confidential transmissions at the eavesdropper, the AN sequences are transmitted at the PBS by exploiting the excess degrees-of-freedom offered by its massive antenna array and by using random AN shaping matrices. The channel estimates at the PBS and secondary base-station (SBS) are obtained by using non-orthogonal pilot sequences transmitted by the primary user nodes (PUs) and secondary user nodes (SUs), respectively. Hence, these channel estimates are affected by intra-cell pilot contamination. In this context, the detrimental effects of intra-cell pilot contamination and channel estimation errors for physical layer secure communication are investigated. For this system set-up, the average and asymptotic achievable secrecy rate expressions are derived in closed-form. Specifically, these performance metrics are studied for imperfect channel state information (CSI) and for perfect CSI, and thereby, the secrecy rate degradation due to inaccurate channel knowledge and intra-cell pilot contamination is quantified. Our analysis reveals that a physical layer secure communication can be provisioned for both primary and secondary massive MIMO systems even with the channel estimation errors and pilot contamination.

A power reduction method for pilot channel of LEO satellite based on dynamic compensation

Since the lower power requirement of code division multiple access (CDMA) than that of other multiple access, the CDMA technology is suitable to be used in low earth orbit (LEO) satellite communication system whose space power is limited due to the small size of satellite. The pilot channel of CDMA technology is very important for earth mobile station (EMS) in LEO system to recover carrier and code, but the power requirement of pilot channel is very higher than that of other channels. In this paper, a power reduction method for pilot channel is proposed. By the new method, the power of pilot channel transmitted from LEO satellite is reduced to a lower level. For improving the signal to noise ratio (SNR) of pilot channel with lower power, coherent integration is employed in EMS at the pre-processing stage. Considering the high dynamic situation of LEO satellite, the long period of time for integration will deteriorate the receiving performance of EMS, therefore, a dynamic compensation module is added to carrier tracking loop against the high dynamic. Meanwhile, the transfer function of the new tracking loop and the condition for steady-state zero error are deduced. Numerical examples are provided to demonstrate effectiveness of the proposed approach.

Channel Rectification and Signal Estimation Based on EIV Model in Massive MIMO System

The performance of Massive MIMO is severely limited by channel estimation error, which is caused by pilot contamination and channel aging. In this paper, we propose an estimation algorithm based on the weighted total least-squares method with errors-in-variables (EIV) model to alleviate the influence of pilot contamination and channel aging. Then, a channel rectification method has been investigated to diminish the inaccuracy of channel estimation. Comparing with the traditional methods, it not only helps to make the signal estimation more accurate, but also provides opportunities to correct the channel model with estimation error and update the aged channel statement information. Simulations are provided to verify the efficacy of this method.

Compose Binary Matrices

Hadamard Matrices and M-Sequences (which formed a closed sets under the addition and with the corresponding null sequence formed additive groups and generated by feedback registers) are used widely at the forward links of communication channels to mix the information on connecting to and at the backward links of these channels to sift through this information is transmitted to reach the receivers this information in correct form, specially in the pilot channels, the Sync channels, and the Traffic channel. This research is useful to generate new sets of sequences (which are also with the corresponding null sequence additive groups) by compose Hadamard matrices and M-sequences with the bigger lengths and the bigger minimum distance that assists to increase secrecy of these information and increase the possibility of correcting mistakes resulting in the channels of communication.

SSCM: An Unambiguous Acquisition Algorithm for CBOC Modulated Signal

Composite binary offset carrier (CBOC) signal has been widely researched in GNSS. The main ingredient of CBOC signal is BOC(1,1) signal. Usually, the acquisition method for BOC(1,1) signal is used to capture CBOC signal, while the research of special acquisition method for CBOC signal is rare. In this letter, according to the principle and characteristics of CBOC signal, a special side-peak cancellation method (SSCM) is proposed and simulated. In this method, two special auxiliary signals are introduced. And the local reference signals are obtained by multiplying the data channel signal and pilot channel signal by the auxiliary signals. The cross-correlation results from the received pilot signal and the two local pilot signals with different auxiliary signals will subtract from one another. Then, side peaks of correlation function and in-band noise of pilot channel are suppressed, while the data channel has the same operation results. At last the outputs of pilot channel and data channel will be added up to make full use of the received signal power. By this way, the acquisition efficiency, accuracy, and adaptability to low signal-to-noise ratio (SNR) conditions for CBOC signal have been improved, alongside possible solution when the GNSS receiver works in a critical environment.

Generalization of Hadamard Matrices

Hadamard’s matrices are used widely at the forward links of communication channels to mix the information on connecting to and at the backward links of these channels to sift through this information is transmitted to reach the receivers this information in correct form, specially in the pilot channels, the Sync channels, the traffic channel and so much applications in the fields; Modern communication and telecommunication systems, signal processing, optical multiplexing, error correction coding, and design and analysis of statistics. This research is useful to generate new sets of orthogonal matrices by generalization Hadamard matrices,with getting bigger lengths and bigger minimum distance by using binary representation of the matrices that assists to increase secrecy of these information, increase the possibility of correcting mistakes resulting in the channels of communication, giving idea to construct new coders and decoders by mod p with more complexity for using these matrices and derivation new orthogonal codes or sequences.

Uplink Spectral Efficiency Analysis of Distributed Massive MIMO with Channel Impairments

In this paper, considering the practical channel impairments known as pilot contamination and channel aging induced by both Doppler shift and phase noise, we analyze the uplink spectral efficiency of multi-cell multi-user distributed massive multi-input multi-output (MIMO) systems with linear receivers. A joint channel model is first provided, which allows studying the impacts of these impairments on the achievable rate performance of distributed massive MIMO systems simultaneously. Based on this model, using the properties of Gamma distributions together with the approximate methods for non-isotropic vectors, we derive tractable but accurate closed-form expressions for the uplink achievable rate with maximum ratio combining (MRC) and zero-forcing (ZF) receivers in distributed massive MIMO systems. User ultimate achievable rate is also given when the ratio of total number of transmit antennas to the number of users is very large. It is shown that MRC and ZF receivers achieve the same ultimate achievable rate in the presence of the practical channel impairments. Numerical results show that channel aging has a greater impact on ZF receiver and the impact of the Doppler shift is more detrimental than that of the phase noise.

GPS L5 Signal Acquisition and Tracking under Unintentional Interference or Jamming

The GPS signal consists of several signals transmitted at the L1, L2, and L5 carrier frequencies. The signal at L1 = 1575.42 MHz and L2 =1227.6 MHz consists of the civilian C/A code signals with pseudorandom sequences of length 1023 and chipping frequency of 1.023 MHz and the P(Y) code signals of length 1 week and chipping frequency of 10.23 MHz. The new L5 signal is QPSKmodulated, centered on 1176.45 MHz. Its two components have each a different spreading code at chipping frequency of 10.23 MHz. The in-phase component carries the navigation message, at 100 symbols per second (50 bits per second with a convolutional encoder) while the quadrature component, called the pilot channel, carries no message at all. Most GPS receivers, whether military or civilian, are designed in a way that the acquisition of the P(Y) code depends on the acquisition and tracking of the C/A code. Moreover, if the acquisition of the P(Y) code is lost, due to reasons that are explained in the paper, then the reacquisition of the P(Y) code will again depend on the acquisition and tracking of the C/A code. Therefore, for most commercially available receivers, the reliable acquisition and tracking of the C/A code is critical for the entire operation of a GPS receiver. However, it is well-known the vulnerability of the GPS C/A code signal, to unintentional interference or jamming. The main theme of this paper is the reexamination of the GPS C/A code signal acquisition and tracking under the situation of the unintentional interference or jamming. A variety of jamming signals are considered such as: (1) periodic, deterministic; (2) aperiodic, deterministic; and (3) noisy type signals or non-deterministic. However, the majority of vendors are still producing correlator type receivers. As shown by the simulation results of this paper and other previous publications a sliding correlator type of receiver used to acquire and track the C/A code or L5 code can be easily jammed by a similar C/A code replica or L5 code replica at power levels 10 dB or higher above noise power. GAMES, GILS, and GIANT are not the most economically viable solutions in the market to handle GPS protection of the civilian receivers. A maximum likelihood GPS receiver which considers all the signals in the environment can be used to acquire and track successfully the C/A and the L5 GPS signals when the jamming signal power are in the range or 10dB or higher above the noise power. In summary, the direction of designing acquisition and tracking receivers for future C/A L1 code or L5 GPS signals should go towards joint signal acquisition and tracking. There are three main challenges with these types of receivers: (1) algorithm complexity, (2) computational power, and (3) test with real data. All these remain to be studied and analyzes further in the future. I think it is going to be a breakthrough in the state of the art of GPS receivers when these algorithms are ultimately implemented and a lot more work is required to arrive at that point which some of it is going to be published in future publications.

Nonoverlay Heterogeneous Network Planning for Energy Efficiency

In this paper, we introduce nonoverlay microcell/macrocell planning that is optimally designed for improving energy efficiency of the overall heterogeneous cellular network. We consider two deployment strategies. The first one is based on a fixed hexagonal grid and the second one is based on a stochastic geometry. In both of our models, microcells are placed in those areas where the received signal power levels of macrocell common pilot channels are below a certain threshold. Thus, interference between microcells and macrocells is minimized. As a result, addition of microcells increases the achieved number of bits per unit energy. Under such deployment assumptions, we investigate the effects of certain parameters on the energy efficiency. These parameters include the user traffic, the Intersite Distance (ISD), the size of microcells and the number of microcells per macrocell for the grid model, and macrocell density and microcell density for the stochastic model. The results of our performance analyses show that utilizing microcells in a sparse user scenario is worse for the energy efficiency whereas it significantly improves both energy and spectral efficiencies in a dense user scenario. Another interesting observation is that it is possible to choose an optimum number of microcells for a given macrocell density.

Joint Channel Training and Feedback for FDD Massive MIMO Systems

Massive multiple-input multiple-output (MIMO) is widely recognized as a promising technology for future 5G wireless communication systems. To achieve the theoretical performance gains in massive MIMO systems, accurate channel state information at the transmitter (CSIT) is crucial. Due to the overwhelming pilot signaling and channel feedback overhead, however, conventional downlink channel estimation and uplink channel feedback schemes might not be suitable for frequency-division duplexing (FDD) massive MIMO systems. In addition, these two topics are usually separately considered in the literature. In this paper, we propose a joint channel training and feedback scheme for FDD massive MIMO systems. Specifically, we firstly exploit the temporal correlation of time-varying channels to propose a differential channel training and feedback scheme, which simultaneously reduces the overhead for downlink training and uplink feedback. We next propose a structured compressive sampling matching pursuit (S-CoSaMP) algorithm to acquire a reliable CSIT by exploiting the structured sparsity of wireless MIMO channels. Simulation results demonstrate that the proposed scheme can achieve substantial reduction in the training and feedback overhead.

Modeling City-Canyon Pedestrian Radio Channels Based on Passive Sounding in In-Service Networks

Recently, a measurement campaign for characterizing time-variant radio channels in city-canyon environments was conducted along a 2-km-long pedestrian shopping street in Shanghai. A passive sounding approach was adopted where a software-defined-radio platform is used as a receiver (Rx) to record downlink signals transmitted by base stations (BSs) in an in-service Universal Mobile Telecommunications System (UMTS). Channel impulse responses are calculated from the data received in common pilot channels, and a space-alternating generalized expectation–maximization (SAGE) algorithm is applied to estimate delays, Doppler frequencies, and complex attenuations of multipath, which are further grouped into clusters characterized by time-evolving parameters. Based on the observations from a total of 70 BSs, stochastic models are established for composite channel parameters, cluster-level characteristics, and the time variabilities of these parameters. The novelties of the models lie in the passive data acquisition, which leads naturally to superior model ergodicity and higher fidelity than the standard models constructed based on active sounding. Furthermore, the models proposed here also exploit a new channel categorization method that takes into account the realistic impact of system configurations, such as the usage of multiple remote radio units in a single BS.

Compose Walsh’s Sequences and M-Sequences

Walsh Sequences and M-Sequences used widely at the forward links of communication channels to mix the information on connecting to and at the backward links of these channels to sift through this information is transmitted to reach the receivers this information in correct form, specially in the pilot channels, the Sync channels, and the Traffic channel.
 This research is useful to generate new sets of sequences (which are also with the corresponding null sequence additive groups) by compose Walsh Sequences and
 M-sequences with the bigger lengths and the bigger minimum distance that assists to increase secrecy of these information and increase the possibility of correcting mistakes resulting in the channels of communication.

The research and the development of the wide area relaying protection based on fault element identification

The urgent problem of the relaying protection in the modern AC/DC hybrid connected grid and the development of the wide area communication, the information process and the intelligent technology powerfully promotes the development of the technology of the wide area relaying protection (WARP), which has become a research hotspot that attracts extensive attention. Originated from the basic concept of the wide area relaying protection, this paper analyses the advantages, the effects and the functions of the wide area relaying protection. The two main approaches to realize the wide area protection, which are on-line adaptive setting (OAS) principle and fault element identification (FEI), are introduced in this paper. Aimed at improving the performance of the backup protection, the research content and the technology demand of the wide area protection are proposed, meanwhile, the basic principle and the algorithm of the fault element identification are introduced. At last, the scheme of the limited wide area relaying protection based on the existing pilot channel of the main protection is discussed.

An Empirical Random-Cluster Model for Subway Channels Based on Passive Measurements in UMTS

Recently, a measurement campaign for characterizing the channels in underground subway environments was conducted in Shanghai, China. Downlink signals transmitted by 46 universal mobile telecommunication system cells deployed along a 34-km-long subway were collected. Channel impulse responses are extracted from the data received in the common pilot channels, based on which parameters of multipath components are estimated by using a high-resolution parameter algorithm derived using the space-alternating generalized expectation-maximization principle. Multiple time-evolving clusters are obtained, each representing the channel from a remote-radio-unit of a base station to the receiver. Based on a total of 98 time-evolving clusters, channels observed in the station scenario and the tunnel scenario are modeled separately for their distinctive behaviors in many aspects, particularly in the variations of clusters’ trajectories. Intracluster characteristics parameterized by cluster delay and Doppler frequency spreads, $K$ -factor, and dependences among these parameters are investigated. Intercluster parameters, including coexisting cluster number, delay offset, power offset, and cross correlations, are investigated for the station scenario. A path loss model is established for the tunnel scenario.

MODELLING LANDSCAPE MORPHODYNAMICS BY TERRESTRIAL PHOTOGRAMMETRY: AN APPLICATION TO BEACH AND FLUVIAL SYSTEMS

Beach and fluvial systems are highly dynamic environments, being constantly modified by the action of different natural and anthropic phenomena. To understand their behaviour and to support a sustainable management of these fragile environments, it is very important to have access to cost-effective tools. These methods should be supported on cutting-edge technologies that allow monitoring the dynamics of the natural systems with high periodicity and repeatability at different temporal and spatial scales instead the tedious and expensive field-work that has been carried out up to date. The work herein presented analyses the potential of terrestrial photogrammetry to describe beach morphology. Data processing and generation of high resolution 3D point clouds and derived DEMs is supported by the commercial Agisoft PhotoScan. Model validation is done by comparison of the differences in the elevation among the photogrammetric point cloud and the GPS data along different beach profiles. Results obtained denote the potential that the photogrammetry 3D modelling has to monitor morphological changes and natural events getting differences between 6 and 25 cm. Furthermore, the usefulness of these techniques to control the layout of a fluvial system is tested by the performance of some modeling essays in a hydraulic pilot channel.

MODELLING LANDSCAPE MORPHODYNAMICS BY TERRESTRIAL PHOTOGRAMMETRY: AN APPLICATION TO BEACH AND FLUVIAL SYSTEMS

Abstract. Beach and fluvial systems are highly dynamic environments, being constantly modified by the action of different natural and anthropic phenomena. To understand their behaviour and to support a sustainable management of these fragile environments, it is very important to have access to cost-effective tools. These methods should be supported on cutting-edge technologies that allow monitoring the dynamics of the natural systems with high periodicity and repeatability at different temporal and spatial scales instead the tedious and expensive field-work that has been carried out up to date. The work herein presented analyses the potential of terrestrial photogrammetry to describe beach morphology. Data processing and generation of high resolution 3D point clouds and derived DEMs is supported by the commercial Agisoft PhotoScan. Model validation is done by comparison of the differences in the elevation among the photogrammetric point cloud and the GPS data along different beach profiles. Results obtained denote the potential that the photogrammetry 3D modelling has to monitor morphological changes and natural events getting differences between 6 and 25 cm. Furthermore, the usefulness of these techniques to control the layout of a fluvial system is tested by the performance of some modeling essays in a hydraulic pilot channel.

New formulation of GNSS acquisition with CFAR detection

Summary This paper deals with the analysis of the acquisition process performed by a global navigation satellite system (GNSS) receiver with a pilot and data channel or in case of GNSS hybrid receiver. Signal acquisition decides the presence or absence of GNSS signal by comparing signal under test with a fixed threshold and provides a code delay and a Doppler frequency estimation, but in low signal conditions or in a noisy environment; acquisition systems are vulnerable and can give a high false alarm and low detection probability. Firstly, we introduce a cell-averaging-constant false alarm rate (CFAR) then a data-pilot cell-averaging-CFAR detector fusion based to deal with these situations. In this context, we use a new mathematical derivation to develop a closed-form analytic expressions for the probabilities of detection and false alarm. The performances of the proposed detector are evaluated and compared with a non-CFAR case through an analytical and numerical results validated by Mont Carlo simulations. Copyright © 2016 John Wiley & Sons, Ltd.

Empirical Geometry-Based Random-Cluster Model for High-Speed-Train Channels in UMTS Networks

In this paper, a recently conducted measurement campaign for high-speed-train (HST) channels is introduced, where the downlink signals of an in-service Universal Mobile Terrestrial System (UMTS) deployed along an HST railway between Beijing and Shanghai were acquired. The channel impulse responses (CIRs) are extracted from the data received in the common pilot channels (CPICHs). Within 1318 km, 144 base stations (BSs) were detected. Multipath components (MPCs) estimated from the CIRs are clustered and associated across the time slots. The results show that, limited by the sounding bandwidth of 3.84 MHz, most of the channels contain a single line-of-sight (LoS) cluster, and the rest consists of several LoS clusters due to distributed antennas, leaking cable, or neighboring BSs sharing the same CPICH. A new geometry-based random-cluster model is established for the clusters' behavior in delay and Doppler domains. Different from conventional models, the time-evolving behaviors of clusters are characterized by random geometrical parameters, i.e., the relative position of BS to railway, and the train speed. The distributions of these parameters, and the per-cluster path loss, shadowing, delay, and Doppler spreads, are extracted from the measurement data.

CPC-based backward-compatible network access for LTE cognitive radio cellular networks

Network access plays an important role in LTE cognitive radio (LTE-CR) cellular networks in determining users’ experiences. An overview is first carried out on network access schemes in existing cognitive cellular networks such as IEEE 802.22 and IEEE 1900.4, based on which it can be seen that cognitive pilot channel (CPC)-based network access is a promising scheme for LTECR, which may provide fast network access and put no stringent requirements on terminals. Next, considering the implementation issues of CPC in practical systems, a CPC-based backward- compatible network access scheme should be designed for LTE-CR to facilitate the application of CR in LTE networks, which could exploit existing LTE structures and technologies to carry CPC information. To achieve this, a new system information block (SIB) should be designed to carry CPC on a current physical downlink shared channel with little standards effort. Moreover, load awareness is introduced so that LTE-CR is activated only when the system load is high. The complete process of this SIB-CPC-based backward-compatible and loadaware network access is described, and its performance is evaluated via simulations. It is shown that the blocking ratio of LTE-CR can be reduced notably compared to that of conventional LTE without CR. Moreover, by selecting an appropriate load threshold to activate LTE-CR, the average user throughput of LTE can be improved with near-zero blocking ratio by offloading users to complementary cognitive spectra.

Random Pilot Signal Design and Channel Estimation Method based on Compressed Sensing Theory

A channel parameter estimation method adapted to a wireless communication system is proposed. The wireless communication system includes a transmitter and a receiver. The proposed method includes following steps. The transmitter transmits a plurality of pilot signals to the receiver by using one of a plurality of preconfigured sparse random pilot patterns. The receiver receives the pilot signals, performs a channel parameter estimation on the pilot signals by using a compressive sensing algorithm to obtain a multipath channel number, and selects a pilot pattern for a next cycle among the preconfigured sparse random pilot patterns according to the multipath channel number and a current pilot number. Additionally, the receiver transmits feedback information associated with the selected pilot pattern to the transmitter.