Channel State Information Reference Signal Research Articles

Research on Fingerprint and Hyperbolic Fusion Positioning Algorithm Based on 5G Technology

With the development of the Internet of Things technology, higher requirements are put forward for the positioning accuracy of objects. This paper presents an indoor fusion positioning algorithm based on the 5th Generation Mobile Communication Technology (5G), which effectively solves two problems. The first is that fingerprint positioning is susceptible to environmental changes and results in inaccurate fingerprint matching. The second is the problem of the hyperbolic positioning algorithm based on the line-of-sight fluctuating too much in complex indoor environments. This paper uses a 5G flexible subcarrier interval of Orthogonal Frequency Division Multiplexing (OFDM) to significantly reduce the time delay error of Time Of Arrival (TOA), and an improved genetic algorithm and the weighted hyperbolic algorithm are used to estimate the optimal position coordinates. In the offline database establishment stage of fingerprint positioning, the Channel State Information-reference signal (CSI-RS) of multiple-beam sets provides high-dimensional information for subsequent training and prediction. The online stage cooperates with the improved residual network model to make predictions. Finally, the positioning information and the error distribution function generated by the two positioning processes are simultaneously used as the input of the Kalman filter to obtain the precise position coordinates. The simulation results show that in complex indoor scenes where line-of-sight propagation and non-line-of-sight propagation paths are mixed, the accuracy of this method can reach below 0.82 m. Thus, the positioning accuracy is significantly improved compared with other methods, which can meet most indoor scene positioning needs.

Downlink transmission and channel estimation for cell-free massive MIMO-OFDM with DSDs

In a cell-free massive MIMO system, multiple users arrive at multiple access points at separate times, while in an OFDM system, different delays can be equivalent to delay spread differences (DSDs). Since DSDs are not all the same, in the downlink transmission process, it is necessary to consider its impact on transmission techniques, such as channel estimation and downlink precoding. In this paper, aiming at the performance loss caused by DSDs in cell-free massive MIMO-OFDM system, we propose a multi-RB precoding optimization algorithm that maximizes the downlink sum rate. We derive the sum rate maximization problem into an iterative second-order cone programming form to achieve convex approximation. Then, considering the impact of DSDs on the accuracy of cell-free massive MIMO-OFDM channel estimation, we propose a downlink channel estimation method, which jointly uses channel state information reference signal and demodulation reference signal. The simulation results show that the proposed multi-RB optimal precoding can effectively improve the downlink sum rate, and the proposed downlink channel estimation can obtain accurate multi-RB frequency-domain channel parameters.

A Sensing-Based Over-the-Air Phased Array Antennas Phase Calibration Method With Greedy Algorithm

Phase errors of phased array antennas (PAA) can cause gain degradation that necessitates calibration to compensate this effect. Over the air (OTA) calibration methods are promising for avoiding interruption of communication applications for specific calibration conditions. However, typical calibration methods have the assumption that precise knowledge about calibration should be exchanged, such as relative positions and cost function (CF) values, which are difficult to obtain in practical mobile communication systems. To overcome this, a sensing-based OTA calibration method is proposed, in which sensing methods aided by cameras or infrastructure sensors could locate user equipment (UE) and regard it as calibration reference source. Then greedy algorithm (GDA) is integrated into NR (New Radio) beam management process, where UE measures directional Channel State Information-Reference Signals (CSI-RSs) reserved for calibration and feeds back the optimal beam index instead of CF values. Consequently, UE received power is maximized, so as to achieve phase calibration. Simulation results exhibit that even when locating error exists, the proposed method can correct phase errors with a low overhead in terms of reserved NR CSI-RSs.

Soft Mobility: Transparent Handover with Zero Handover Failure in User-Centric Networks

User-centric network (UCN) is regarded as a promising candidate to approach the challenges of more radio link failures (RLFs) due to the ultradense deployment of small base stations (SBSs) and meet the requirements of ultrahigh throughput, ultrahigh reliability, and ultralow latency for the 6G system. In this paper, soft mobility is proposed for UCN with the split of control and user plane (C/U-plane) and shared physical cell identifier (PCI) to achieve the goal of zero handover failure (HOF) probability, where transparent handover (HO) within a cell is realized with user configuration duplication and measurement enhancement. Specifically, the cell is composed of several SBSs around the user, where one anchor SBS is selected for controlling, and others act as slave SBSs for transmission with duplicated UE configuration from the anchor SBS. Based on the proposed architecture, the user measures downlink channel quality for cells and SBSs distinguishingly, via SS/PBCH Block (SSB) and channel-state information-reference signal (CSI-RS), respectively, and then makes the HO decision. Results show that soft mobility can reduce the number of HOF by about 50% over the current system, and the HOF probability is lower than 1% for TTT = 40 ms and offset = − 1 dB.

Downlink Channel Reconstruction for Spatial Multiplexing in Massive MIMO Systems

To get channel state information (CSI) at a base station (BS), most of researches on massive multiple-input multiple-output (MIMO) systems consider time division duplexing (TDD) to get benefit from the uplink and downlink channel reciprocity. Even in TDD, however, the BS still needs to transmit downlink training signals, which are referred to as channel state information reference signals (CSI-RSs) in the 3GPP standard, to support spatial multiplexing in practice. This is because there are many cases that the number of transmit antennas is less than the number of receive antennas at a user equipment (UE) due to power consumption and circuit complexity issues. Because of this mismatch, uplink sounding reference signals (SRSs) from the UE are not enough for the BS to obtain full downlink MIMO CSI. Therefore, after receiving the downlink CSI-RSs, the UE needs to feed back quantized CSI to the BS using a pre-defined codebook to support spatial multiplexing. In this paper, possible approaches to reconstruct full downlink MIMO CSI at the BS are proposed by exploiting both the SRS and quantized downlink CSI considering practical antenna structures with reduced downlink CSI-RS overhead. Numerical results show that the spectral efficiencies by spatial multiplexing based on the proposed downlink MIMO CSI reconstruction techniques outperform the conventional methods solely based on the quantized CSI.

Remote interference management in 5G new radio: methods and performance

In time division duplexing based mobile networks, under certain atmospheric ducting conditions, the uplink reception may be interfered by the downlink transmissions of remote base-stations (gNBs) located hundreds of kilometers away. This paper addresses such remote interference problem in a 5G new radio (NR) macro deployment context. Specifically, two potential reference signal (RS) designs for remote interference management (RIM) are described. The first signal structure, denoted as the one OFDM symbol (1OS) based RIM-RS, is building on the channel state information reference signals of 5G NR. The second candidate is referred to as the two OFDM symbol based RIM-RS design, which builds on the design principles of LTE RIM-RS. The achievable detection performance is evaluated by introducing enhanced receiver algorithms together with three feasible propagation delay based gNB grouping and corresponding RIM-RS transmissions schemes. The performance results in terms of the receiver processing gain highlight that the improved detection algorithm assures sufficient performance to detect the remote interference for both RIM-RSs with all evaluated frequency domain comb-like patterns. The benefit of grouping corresponding RIM-RS transmissions from gNBs located on the same area is greater when using same frequency domain resources per transmitted sequence in practical interference scenarios. Furthermore, applying a common base sequence for all gNBs within a group allows to identify the group based on detected sequence and enables adaptive RIM mitigation schemes. On the other hand, it is shown that the 1OS RIM-RS provides smaller overhead and can be frequency multiplexed with the physical downlink shared channel, which opens up the possibility of using gNB group wise 1OS RIM-RS also for UE interference measurements.

Measurement-Based Channel Characterization for 5G Downlink Based on Passive Sounding in Sub-6 GHz 5G Commercial Networks

Under the impetus of global communications organizations, 5G mobile communications becomes a hot technology and moves towards commercial use. In this paper, we propose an efficient downlink channel characterization scheme based on passive sounding in sub-6 GHz 5G commercial network. We first introduce the framework of passive sounding system containing a space-time-division multiplexing (STDM) sounder. Then we elaborate the extraction procedure for 5G downlink signals including synchronization signal block (SSB) and channel state information reference signal (CSI-RS) according to New Radio (NR) technical specifications proposed by 3GPP. Through a pilot test in the anechoic chamber, we also demonstrate the practice of signal extraction. Besides, we derive a dual-polarimetric space-alternating generalized expectation-maximization (SAGE) algorithm which matches with the passive sounding system for multi-dimensional channel parameter estimation. The estimator performance is analyzed by synthetic channel simulation, and results reveal its high accuracy and robustness. Finally, we verify the feasibility of the proposed scheme through analyzing channel characteristics derived from passive sounding in stationary field measurements respectively conducted in industrial park and parking lot with the 5G commercial network built by China Unicom Communications Corporation (CUCC).

Hybrid Neural Network-Based Fading Channel Prediction for Link Adaptation

We propose an artificial intelligence-based channel prediction scheme that can potentially facilitate link adaptation in customized communication systems. Link adaptation is a key process for wireless communication that requires accurate channel state information (CSI). However, the CSI may be outdated because of computational and propagation delays. In addition, a subframe with no CSI reference signal cannot provide CSI feedback. The proposed scheme solves these problems by predicting future channels. Although traditional stochastic methods suffer from marginal prediction accuracy or unacceptable computational complexity, neural networks allow time series prediction for channels even considering constraints for practical application. We introduce a hybrid architecture for improving the prediction accuracy of the neural network when extracting meaningful features. The proposed scheme uses a single hybrid network that can predict channels in different environments. Simulations were performed using a spatial channel model to evaluate the performance at the system-level, and the results indicated that the proposed scheme effectively increases the prediction accuracy for the channel quality indicator and spectral efficiency.

Enhanced CSI Acquisition for FDD Multi-User Massive MIMO Systems

Massive multiple-input multiple-output (MIMO) is envisioned to meet the growing spectral efficiency (SE) requirement in next generation cellular systems. However, it has been recognized that the unaffordable channel state information reference signal (CSI-RS) overhead required for acquiring CSI is a major challenge in frequency division duplexing (FDD) massive MIMO systems. To tackle the challenge of this CSI-RS overhead limitation, certain attempts, which have been designed for the scenarios with dispersive locations of users and sparse nature of channels, suffer from inaccurate channel estimation when the nature of channels for different users becomes highly correlated and rich. In this paper, we propose an enhanced CSI acquisition scheme for FDD multi-user massive MIMO systems, which exploits beamformed CSI-RS transmission mechanism to reduce the CSI-RS overhead. We present two limited feedback algorithms which provide different tradeoffs between system performance and CSI feedback overhead, where the multistage CSI acquisition strategy is adopted to avoid prohibitive computational complexity and amount of feedback requirement. The simulation results show that our CSI acquisition scheme, without additional CSI-RS overhead and enormous CSI feedback overhead, achieves higher SE performance as compared to conventional scheme.

주파수 분할 방식의 거대 다중 안테나 시스템을 위한 빔형성 기반의 채널상태정보 기준신호 전송기술

기존 MIMO 시스템 대비 수십 또는 수백 배 많은 송신 안테나들이 설치되어 있는 주파수 분할(frequency division duplex, FDD) 방식의 거대 다중 안테나(massive multiple-input mulitple-output, Massive MIMO)에선 송신 안테나 별 CSI-RS(channel state information reference signal) 전송을 위해 기존 MIMO 시스템 대비 너무 많은 하향 및 상향링크 자원 요소가 필요하다는 한계를 갖는다. 이러한 단점들을 극복하기 위해 본 논문에선 주파수 분할 방식의 거대 다중 안테나 시스템에서 많은 송신 안테나를 사용하더라도 자원요소(resource element, RE)를 재사용함으로써 송신 안테나 수에 비례하지 않는 제한된 양의 하향링크 자원만을 사용하여 CSI-RS를 효과적으로 전송하는 기술 및 자원격자 구조를 제안하였다. Since FDD massive MIMO (multiple-input multiple-output) system deploys hundreds of transmit antennas at base station (BS) compared to conventional MIMO system, the overhead of transmitting channel state information reference signal (CSI-RS) increases proportionally to the number of transmit-antennas. To overcome these disadvantages, we proposed beamforming based CSI-RS transmission technique for FDD massive MIMO system which transmit CSI-RS by limited amount of downlink resources.

Transmission Scheme with Limited Channel State Information Feedback for 3D MIMO System

Three-dimensional (3D) multiple-input multiple-output (MIMO) system can exploit the spatial degree of freedom in vertical dimension and can significantly improve system performance compared with 2D transmission scheme. However, in the actual frequency division duplex (FDD) transmission mode, the large overhead of the reference signal and channel state information (CSI) feedback would become a barrier for performance improvement of 3D MIMO system with the significantly increased number of transmit antennas. To deal with these problems, this paper proposes a new transmission scheme of the channel state information-reference signal (CSI-RS), where the CSI-RS is precoded with 3D beamforming vectors and composed of two components: long-term CSI-RS and short-term CSI-RS. For the purpose of conducting efficient transmission in widely used FDD system, we also propose a corresponding limited channel state information feedback scheme. Moreover, multiuser pairing and scheduling criteria based on the design of the CSI-RS are proposed to realize the multiuser transmission. We have investigated multiple options for 3D MIMO codebook scheme and finally adopt the Kronecker product-based codebook (KPC) for precoding operation at the base station (BS). Simulation results demonstrate that our proposed scheme for the 3D MIMO system achieves a better tradeoff between resource overhead and throughput performance.

Evolution of reference signals for LTE-advanced systems

3GPP LTE Release 10 standards (also known as LTE-Advanced) adopted some of the state-of-the-art radio access technologies that include carrier aggregation, eight-layer downlink spatial multiplexing, and four-layer uplink spatial multiplexing. For facilitating these enhancements, reference signals have significantly evolved in LTE-Advanced. This article examines underlying design principles of the LTE-Advanced reference signals. Specifically, newly introduced dedicated demodulation reference signals and channel state information reference signals for downlink and improvements of demodulation reference signals and sounding reference signals in uplink are discussed.

Investigation on Data Signal Muting to Improve Channel Estimation Accuracy in Downlink Coordinated Multiple-Point Transmission in LTE-Advanced

Accurate channel estimation for multiple cells is essential in downlink coordinated multi-point (CoMP) transmission/reception. Therefore, this paper investigates a technique to improve the channel estimation for downlink CoMP in Long-Term Evolution (LTE)-Advanced. In particular, the performance of data signal muting, i.e., muting data signals that collide with the channel state information reference signal (CSI-RS) of a neighboring cell, is evaluated considering various CoMP schemes and intra-eNodeB and inter-eNodeB CoMP scenarios. In a multi-cell link level simulation, coordinated scheduling and coordinated beamforming (CS/CB) CoMP is employed. The simulation results show that data signal muting is effective in improving the channel estimation accuracy, which is confirmed by numerical analysis. Simulation results also show that it is effective in improving the throughput performance, especially for sets of user equipment at the cell boundary. Furthermore, the tradeoff relationship between accurate channel estimation by muting larger numbers of data signals and a high peak data rate, i.e., low overhead, is investigated. It is shown that when the number of coordinated cells is set to three, the CSI-RS reuse factor is set to three, and the well-planned CSI-RS pattern allocation is employed, the improvement in performance is almost saturated in a synchronized network.