Orthogonal Pilot Sequences Research Articles

Analysis and optimization for non-orthogonal pilot sequence sets in massive MIMO systems

In modern wireless communication systems, orthogonal pilot signals has been generally employed in estimation of the channel state information. However, orthogonal pilot signals are inadequate for supporting the rapidly increasing requirements of communication throughput for 5G-and-beyond wireless environments, owing to the pilot contamination and short coherence times in high-mobility situations. To address these concerns, we present a new strategy for making use of non-orthogonal pilot sequences in channel estimation for multi-cell massive multiple-input multiple-output systems. First, we extend prior pilot assignment strategies based on the orthogonality of pilots to the general case of non-orthogonal pilot signals. Based on the proposed non-orthogonal pilot assignment strategy, we establish the minimal pilot length that fulfills a requirement for the channel estimate error, under a given degree of non-orthogonality. Then, we demonstrate validity of the pilot assignment strategy with the minimal length, which maximizes the entire network throughput. Simulation results show that our proposed method gives a significantly enhanced performance in terms of the net throughput compared to that with orthogonal pilot sequences. The performance gain becomes particularly significant with a higher density of users or shorter coherence time intervals.

Location-aided user selection and sum-rate analysis for mmWave NOMA

In this paper, we propose a user selection scheme based on location-aided interference prediction to reduce the training overhead in a non-orthogonal multiple access (NOMA) system. First, we cluster the users based on their location information, enabling the use of non-orthogonal pilot sequence within a cluster and orthogonal pilot sequence between different clusters to reduce the uplink pilot training length. Secondly, we exploit the location information in the computation of the covariance matrices, enabling the prediction of the interference between users. The predicted interference is employed to select the set of users with minimum interference for uplink channel estimation and downlink NOMA data transmission. Finally, the achievable sum-rate of the massive multiple-input multiple-output millimeter wave NOMA system is analyzed. The analytical and numerical results reveal that the location information can be exploited for user selection to reduce the effect of pilot contamination, enhancing the uplink channel estimation and downlink achievable sum-rate.

Estimation of bit error rate in 2×2 and 4×4 multi-input multi-output-orthogonal frequency division multiplexing systems

<span lang="EN-US">Multiple-input, multiple-output orthogonal frequency-division multiplexing (MIMO-OFDM) systems with multiple input antennas and multiple output antennas in dynamic environments face the challenge of channel estimation. To overcome this challenge and to improve the performance and signal-to-noise ratio, in this paper we used the Kalman filter for the correct estimation of the signal in dynamic environments. To obtain the original signal at the receiver end bit error rate factor plays a major role. If the signal to noise ratio is high and the bit error rate is low then signal strength is high, the signal received at the receiver end is almost similar to the </span><em><span lang="EN-US">i<sup>th</sup></span></em><span lang="EN-US"> transmitted signal. The dynamic tracking characteristic of Kalman filter is used to establish a dynamic space-time codeword and a collection of orthogonal pilot sequences to prevent interference among transmissions in this paper. Using the simulation, the Kalman filter method can be compared to the other channel estimation method presented in this paper that can track time-varying channels rapidly.</span>

Covariance-Based Activity Detection With Orthogonal Pilot Sequences for Cell-Free Distributed Massive MIMO Systems

The grant-free random access (GFRA) has been the mainstream access scheme in the massive ultra-reliable low-latency communications (mURLLC). Device activity detection is the foremost issue in GFRA. Most of previous works assume unique non-orthogonal pilot sequence assignment in device activity detection which brings about severe inter-device interference and requires high-complexity access point (AP) coordination to eliminate interference. Taking advantage of the good cross-correlation characteristic of orthogonal pilot sequences and the sparsity in power domain of cell-free (CF) distributed massive multiple-input multiple-output (mMIMO) systems, this paper proposes a novel orthogonal pilot sequences based activity detection (OPSAD) algorithm to alleviate inter-device interference and thus improve device activity detection performance. In the proposed OPSAD algorithm, the min-max covariance interference (MMCI) pilot assignment algorithm considering AP selection and power control is introduced and a new interference metric is defined to efficiently capture the inter-device interference in this algorithm. Simulation results show that the proposed algorithm reduces computational complexity and achieves better performance than the benchmark algorithm utilizing non-orthogonal pilot sequences in practical mURLLC scenario.

Downlink Resource Allocation With Pilot Length Optimization for User-Centric Cell-Free MIMO Networks

Pilot length is a crucial parameter in cell-free multiple-input multiple-output (MIMO) networks, which could significantly affect the downlink throughput. In this letter, we jointly optimize the user scheduling, power allocation and pilot length for user-centric (UC) cell-free MIMO networks. We consider the frequency band is uniformly split into several sub-channels. As the number of users scheduled on one sub-channel is commonly small, orthogonal pilot sequences are adopted among users on each sub-channel to avoid pilot contamination. To achieve user fairness, we aim to maximize the minimum ergodic user rate in the downlink transmission, yielding a challenging mix-integer non-convex optimization. Inspired by the weighted <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$l_{1}$ </tex-math></inline-formula> -norm approximation in compressive sensing together with successive convex approximation (SCA), an iterative scheme is then proposed to solve the problem. Simulation results demonstrate that the proposed scheme outperforms its state-of-the-art counterpart, which is a three-step algorithm including user grouping, sub-channel allocation, and power optimization.

Spatial Multiplexing Superimposed Pilots for Multicell Multiuser MIMO Uplink Systems

For a multiple-input multiple-output (MIMO) system, or a multiuser MIMO system, it is important to acquire the accurate channel state information. In this article, a superimposed-pilot-based channel estimation scheme is proposed for multicell multiuser MIMO uplink systems. In this scheme, the pilot sequences and data sequences are superimposed, but the space generated by the pilot sequences and the space spanned by data sequences are separated far enough in order to reduce interference. Based on this scheme, the minimum mean-square error channel estimation is deduced, and the optimal power allocation between the pilots and the data signals is derived to maximize throughput. These results show that our proposed scheme can overcome the pilot contamination and achieve better performance than the traditional time-multiplexing scheme with mutually orthogonal pilot sequences for different users when the coherent time slot is limited.

Large-Scale Fading Coefficients Classification-Aided Power Control Strategy for Mitigating the Pilot Contamination in Massive MIMO Systems

Deploying base stations with a massive number of antennas give birth to massive multi-input multi-output technology, which can boost the quality of the wireless communication; however, the limitations imposed by the length of the coherence interval has, directly, limited the number of the orthogonal pilot sequences (OPSs) that can be exploited for acquiring such accurate channel state information at each base station (BS). Hence, the available pilot resources are reused among several cells, which causes the problem of pilot contamination (PC). In this paper, the PC problem is analyzed, and by exploiting the large-scale fading coeffificients of the users’ equipment (UEs), we have classifified the users within each cell; therefore, the same OPS is, solely, reused by the far-distant UEs; hence, the inflfluence of the PC problem is made as small as possible. Since the UEs are subject to different channel conditions, we have consolidated our proposal by a power control algorithm, which boosts the performance of our proposal. Simulation results prove the effectiveness of our proposed decontaminating strategy.

Pilot Contamination Mitigation in Massive MIMO Cloud Radio Access Networks

Massive multiple-input multiple-output (MIMO) technology is expected to achieve significant gains in both signal-to-noise-plus-interference ratio (SINR) and throughput for 5G cellular wireless networks. Efficient and highly accurate channel state information (CSI) acquisition at the base stations (BS) is essential to achieve the potential benefits of massive MIMO systems. However, the inadequate number of orthogonal pilot sequences used for CSI estimation leads to erroneous channel estimation as it causes interference between pilot sequences. This phenomenon is coined pilot contamination and severely limits the system performance. Therefore, we address in this paper the pilot contamination problem in massive MIMO Cloud-Radio Access Networks systems. Leveraging on a real telecom operator data delivered by Call Detail Records (CDR), our objective is to maximize the average uplink achievable rate by reducing the effect of pilot contamination in massive MIMO Cloud-Radio Access Networks (C-RAN). As such a problem is a non-linear integer problem that has no solution in polynomial time, we develop a two-stage solution to solve it. First, a coalition game is proposed where Remote Radio Heads (RRHs) gather into clusters with random user-pilot allocation. Then, two greedy heuristics are applied to match each user in the cluster with a given pilot. The goal is to further improve the average uplink rate achieved in the first stage. Simulation results show that our heuristic solutions for pilot contamination mitigation outperform the traditional pilot allocation solution and a state-of-the-art pilot allocation scheme based on large-scale fading in terms of average uplink achievable rate and SINR.

Ant colony‐based strategy to mitigate the pilot contamination problem in multicell massive multiple‐input multiple‐output systems

AbstractDue to its ability to serve a large number of the user equipments (UEs), massive multiple‐input multiple‐output (mMIMO) technology has been elected to meet the requirement of the upcoming new five‐generation systems. Despite its advantages, mMIMO is still obstructed by the pilot contamination (PC) problem, which is birth from, simultaneously, reusing the same orthogonal pilot sequences (OPSs) across several cells. Due to the scarcity of the OPSs, it is necessary to properly allocate the available OPSs to the UEs. Specifically, the available OPSs should be assigned to the UEs while the severity of the PC problem, between the UEs that employ the same pilot sequences, remains as small as possible. To reach that goal, we have employed the ant colony‐based optimization (ACO) algorithm to find the best pattern in which the severity of the PC problem is reduced among all the UEs. In a nutshell, a graph that sizes the strength of the PC among the UEs is constructed; therefore, the ACO algorithm is employed to connect every two UEs that causes to each other the highest influence of the PC, therefore, the UEs are, successively, assigned with the available OPSs where the severity of the PC is significantly reduced.

Identification of active users for grant-free massive connectivity in large scale antenna systems

Conventional grant-based random access scheme is inappropriate to massive Internet of Things (IoT) connectivity since massive devices results in large number of collisions. This is unacceptable for the low latency requirement in 5 G and future networks. It is also not possible to assign orthogonal pilot sequences to all users to perform user activity detection (UAD) due to the massive number of devices and limited channel coherence time. In this paper, a novel grant-free (GF) UAD scheme is proposed with extremely low complexity and latency in an IoT network with a massive number of users. We exploit multiple antennas at the base station (BS) to produce spatial filtering by a fixed beamforming network (FBN), there then the inter-beam interference can be mitigated. Moreover, intra-beam interference is removed in temporal domain by orthogonal multiple access (OMA) technology. Joint UAD and multiuser detection (MUD) is realized by a bank of spatial-temporal matched filters at BS. The proposed method is efficient and the complexity is much less than the existing compressed sensing (CS)-based GF non-orthogonal multiple access (GFNOMA) algorithms. Performances of the proposed method is extensively analyzed in terms of the successful activity detection rate (SADR) as well as the Receiver operating characteristic (ROC) based on Neyman-Pearson (NP) decision rule. Numerical results demonstrate that it is comparable to the recently proposed iterative Maximum Likelihood (ML) algorithm, yet the computation load of the proposed scheme is extensively reduced.

URLLC With Massive MIMO: Analysis and Design at Finite Blocklength

The fast adoption of Massive MIMO for high-throughput communications was enabled by many research contributions mostly relying on infinite-blocklength information-theoretic bounds. This makes it hard to assess the suitability of Massive MIMO for ultra-reliable low-latency communications (URLLC) operating with short-blocklength codes. This paper provides a rigorous framework for the characterization and numerical evaluation (using the saddlepoint approximation) of the error probability achievable in the uplink and downlink of Massive MIMO at finite blocklength. The framework encompasses imperfect channel state information, pilot contamination, spatially correlated channels, and arbitrary linear spatial processing. In line with previous results based on infinite-blocklength bounds, we prove that, with minimum mean-square error (MMSE) processing and spatially correlated channels, the error probability at finite blocklength goes to zero as the number <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$M$ </tex-math></inline-formula> of antennas grows to infinity, even under pilot contamination. However, numerical results for a practical URLLC network setup involving a base station with <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$M=100$ </tex-math></inline-formula> antennas, show that a target error probability of 10 <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">−5</sup> can be achieved with MMSE processing, uniformly over each cell, only if orthogonal pilot sequences are assigned to all the users in the network. Maximum ratio processing does not suffice.

Pilot contamination mitigation under smart pilot allocation strategies within massive MIMO-5G system

Within massive multiple-input-multiple-output (Massive MIMO) system, pilot contamination (PC) is deemed as a stumbling block in boosting the spectral efficiency (SE) regarding fifth-generation (5G) wireless communication network. To alleviate efficacy of PC, efficient sectorization-based pilot allocation (ES-PA) scheme is recommended, here users equipment (UE) are divided corresponding to their signal-to-interference-plus-noise-ratio (SINR) within two zones, i.e., cell center zone and edge zone. Smart antenna technique is used to split up edge zone further into N uniform sectors. The UE present in the cell center zone are allotted with identical pilot sequences on account of lower inter-cell-interference (ICI), whereas UE present in each sector of edge zone is allotted with mutually orthogonal pilot sequences to diminished PC. The simulation results illustrates that this recommended approach substantially attenuate strength of PC, avail lower mean squared error (MSE), greater data rate and superior SE as compared to conventional pilot allocation methods. In another effective proposed scheme II for mitigating PC, all active users are initially classified between high interference UH and low interference UL users premised on their large scale-fading. An efficient pilot allocation approach in accordance with edge weighted interference graph (EWIG) is recommended to clarify low interference users UL. Simulation output reveals that recommended scheme II upgrade both uplink achievable rate (R) and SINR. Additionally, the recommended approach is considerably competent of mitigating PC and maximizing system performance.

Low complexity channel estimation algorithm using paired spatial signatures for UAV 3D MIMO systems

This paper proposes a low complexity channel estimation algorithm for unmanned aerial vehicle three dimension multi-user multiple-input-multiple-output (3D MIMO) systems with the uniform planar array (UPA) at base station using paired spatial signatures. With the aid of antenna array theory and array signal processing, 3D channel is firstly modeled based on the angles between the direction of arrival along x- and y-axis of the UPA. And 3D MIMO channels can be projected onto the x- and y-directions, respectively. Then, channel estimation for multi-user uplinks using small amount of training resources is divided into two phases. At the first uplink preamble phase, each user is assigned the orthogonal pilot, and the paired spatial signatures and optimal rotation angle of each user through the same pilot sequence are obtained. We also propose a user grouping strategy based on three-dimension angle-division multiple access (3D-ADMA) to ensure that the user's spatial signatures do not overlap. At the second phase during several coherence times, the same pilot sequence within a group and orthogonal pilot sequences between groups are assigned, then, the channel state information of the user's x- and y-directions are recovered by the paired space signatures and optimal rotation angle of each user obtained in the preamble phase, respectively. And dynamically updating the user's paired spatial signatures and optimal rotation angle utilizes the obtained channel parameter of x- and y-directions. Finally, the channel parameter of the x- and y-directions are reconstructed by the updated user's space signatures and the optimal rotation angle, and the 3D MIMO channel estimation is obtained through the Kronecker product. Compared with the conventional channel estimation method of the 3D MIMO system under UPA using a low-rank model, the proposed methods reduce the computational complexity without degrading the estimated performance to a large extent. Furthermore, it is carried out with limited training resources, and the pilot resource overhead of the system is greatly reduced by the 3D-ADMA packet and the two-stage pilot allocation. Simulation results verified that the proposed algorithm is effective and feasible.

Encryption Based Strategy to Overcome the Problem of Pilot Contamination Within Multi-cellular Massive MIMO Systems

The problem of inter-cell interferences keeps its site as the most challenging constraint that faces the massive multi-input multi-output (M-MIMO) technology. This constraint, known as the problem of pilot contamination (PC), is a direct result of reusing the same set of orthogonal pilot sequences (OPSs) across several cells, due to the scarcity of available pilot resources, compared to the number of the user equipments (UEs) that must be served, the reuse of the same OPSs within different cells is unavoidable. Accordingly, assigning the available OPSs to the UEs should be managed to address the PC problem. To reach that goal, a new decontaminating strategy is proposed herein, which is referred to as the ENCryption-based decontaminating strategy (ENC). The ENC strategy is based on injecting some recognition pilot symbols within the pilot sequence of the UEs; hence, the base stations become able to distinguish between the desired pilot signals from the undesired ones, therefore, the quality of servicecan be enhanced, furthermore, the proposed ENC strategy is of low computational complexity compared to the existing strategies.

Estudio y simulación de técnicas para reducir la PAPR en HACO-OFDM

VLC (Visible Light Communications) have been recently proposed as a new form of wireless communications. The VLC advantages are its usage of the spectrum of visible light which is not licensed; additionally, it gives high data rates, protects the user against espionage and does not suffer from interference of the electromagnetic spectrum. One of the main techniques used in VLC is HACO-OFDM (Hybrid Asymmetrically Clipped Optical - Orthogonal Frequency Division Multiplexing), which offers a high spectral efficiency. However, one of its main problems is its high PAPR (Peak-to-Average-Power Ratio). This article presents a study and simulation of Clipping, CE-POCS (Constellation Extension – Project Onto Convex Sets), OPS (Orthogonal Pilot Sequences) and SAP (Simple Amplitude Predistortion) techniques for the reduction of the PAPR in HACO-OFDM systems. The simulation results show that the SAP technique gives the best results in PAPR reduction without significant degradation in the BER (Bit Error Rate).

Selected‐Mapping Peak‐to‐Average Power Reduction Method with Orthogonal Pilot Sequences in Underwater Acoustic OFDM System Without Side Information

A novel Selected-mapping (SLM) Peak-to-average power ratio (PAPR) reduction scheme requires no Side information (SI) in Underwater acoustic (UWA) OFDM system is proposed. In the proposed scheme, every distinct phase sequence is represented by a unique Orthogonal comb pilot sequence (OPS), and the orthogonal properties of the OPSs are used to distinguish the index of phase sequences at the receiver. Therefore, the proposed scheme does not need to reserve bits for transmitting SI, so that the data rate can be raised. Simulation results show that the PAPR reduction performance has almost 0.5dB gains comparing to the Conventional SLM (C-SLM) scheme and the Bit error ratio (BER) performance is approximately the same as the SLM scheme with perfect SI. Field experimental results also demonstrate that the proposed scheme can differentiate phase sequences, therefore significantly enhance the quality of the UWA OFDM communication system.

Interference Cancellation Techniques for Device-to-Device Discovery in Out-of-Coverage Networks

Nowadays, the number of users and connected devices linked to a cellular network is very large. For that reason, new technologies that do not need network support, such as Device-to-Device (D2D) communication, have been developed. D2D communications may occur randomly, uncoordinated and unscheduled, giving rise to interference, which critically impairs the ability of a device to identify its neighbors - a process known as D2D discovery. This work proposes an innovative method to mitigate the interference problem in the D2D discovery process; it is based on a new approach to enhance the detection of multiple concurrent transmitting devices, namely by considering the use of multiple orthogonal pilot sequences jointly with a new receiver block, and on a new procedure that extends the Successive Interference Cancellation (SIC) technique using a single time slot (intra-SIC) to a SIC process that is able to consider several time slots (inter-SIC), which is made possible due to the creation of a new frame concept - the virtual frame. A simulation framework is implemented with the purpose of demonstrating how the proposed method would work and confirm its suitability and effectiveness. It is shown that, for a high number of contending devices and without the use of any type of SIC, about 50% of the discovery sessions are successfully completed; by applying intra-SIC, the discovery success ratio increases to 75%-80%; however, by considering the method proposed herein, 85%-95% of the discovery sessions are successfully completed.

INFLUENCE OF DOPPLER EFFECTS ON 2×2 TO 4×4 MIMO SYSTEMS WITH DIRECT LINE-OF-SIGHT PATH BY RICIAN FADING DISTRIBUTION

Background. For multiplying the capacity of a radio link by using multiple antennas at the transmitter and receiver ends, wireless communication networks use the MIMO technique. The quality of MIMO wireless communication may worsen when either the transmitter or receiver end is in motion, or they both are in motion. To sustain high quality of links, MIMO operates, in particular, on channel state information by using orthogonal pilot sequences.Objective. The goal is to estimate the bit-error-rate performance of 2×2, 3×3, and 4×4 MIMO systems with orthogonal pilot sequences for a range of Doppler shifts by the Rician fading distribution modeling the scenario of direct line-of-sight path. The estimation is believed to answer the question on MIMO efficiency by ascertaining whether increasing the number of antennas mitigates the Doppler effect in 2×2 to 4×4 MIMO systems with direct line-of-sight path.Methods. To achieve the goal, 2×2 to 4×4 MIMO systems with channel state estimation are simulated. The simulation is configured and carried out by using MATLAB® R2019a Communications System ToolboxTM functions. The 35 subcases of the frame length and number of pilot symbols per frame are considered.Results. The near-exponential-type decreasing of the bit-error-rate performance is almost not violated by no motion, whereas further speed increments destroy it for 2×2 MIMO systems. It is revealed that too long packet transmissions by short orthogonal pilot sequences (with respect to the packet length) are prone to errors. This especially concerns 2×2 MIMO systems, where channel state estimation by short orthogonal pilot sequences appears to be ineffective or weakly effective.Conclusions. In general, to maintain an appropriate MIMO link data rate, the packet length should be shortened as the motion speed increases. Increasing the number of antennas additionally mitigates Doppler effects. S o, 4 ×4 M IMO s ystem transmissions are indeed efficient. The shortest possible packet transmissions are not affected by Doppler effects if three or four antennas are used.

User grouping and optimization-based pilot scheduling for mitigating the pilot contamination in massive multi cell MIMO systems

Massive multiple-input multiple-output (massive MIMO) is a promising approach in wireless communication systems for providing improved link reliability and spectral efficiency and it helps several users. The main aim is to solve pilot contamination issue in massive MIMO systems; this research paper utilizes two approaches for reducing the contamination. This paper presents the user grouping approach based on sparse fuzzy C-means clustering (sparse FCM), which groups user parameters based on parameters such as large-scale fading factor, SINR, and user distance. Here, same pilot sequences are assigned to center users in which the impact of pilot contamination is limited, while the algorithm assigns orthogonal pilot sequences to the edge users that suffer severely from pilot contamination. Therefore, the proposed user grouping keeps away from the inappropriate grouping of users, enabling effective grouping even under the worst situations of the channel. Secondly, pilot scheduling is done based on elephant spider monkey optimization (ESMO), which is designed by integrating elephant herding optimization (EHO) into spider monkey optimization (SMO). The performance of pilot scheduling based on grouping-based ESMO is evaluated based on achievable rate and SINR. The proposed method achieves maximal achievable rate of 41.29[Formula: see text]bps/Hz and maximal SINR of 124.31[Formula: see text]dB.

Smart Switching Strategy-Based Supervision Rule to Mitigate the Problem of Pilot Contamination in Massive MIMO Systems

Despite the large benefits that can be fulfilled through the exploitation of Massive Multi-input Multioutput (M-MIMO), this technology still constrained by a well-known constraint, called as pilot contamination problem (PCP), which is the main consequence of, simultaneously, reusing the same set of orthogonal pilot sequences (OPSs) for the users of several cells. Due to the scarcity of the OPS resources, the reuse of the same set of the OPSs for the users of different cells is unavoidable. Hence, this work proposes a novel decontaminating strategy, which is aimed at guaranteeing a trade-off between the use of the OPSs and the mitigation of the PCP. Specifically, to make the use of the available OPSs better, we propose the consolidation of two powerful decontaminating strategies. Under a derived supervision rule (SR), these strategies are the soft pilot reuse-based multicell block diagonalization precoding (SPR-MBDP) and the weighted graph coloring-based pilot assignment (WGC-PA). The SR enables the switching mechanism between the two strategies, which leads to address the PCP with a fewer number of the OPSs compared to the SPR-MBDP, therefore boosting the per-cell achievable rate. Simulation results prove the effectiveness of our proposed strategy.