Data-Driven Deep Learning to Design Pilot and Channel Estimator For Massive MIMO
Advanced Research Institute of Multidisciplinary Science (ARIMS)（多学科科学高级研究院（ARIMS））；School of Information and Electronics, Beijing Institute of Technology (BIT)（北京理工大学信息与电子学院）
Xisuo Ma, Zhen Gao
备注：
6 pages 4 fugures;accepted by IEEE Transactions on Vehicular Technology
In this paper, we propose a data-driven deep learning (DL) approach to jointly design the pilot signals and channel estimator for wideband massive multiple-input multiple-output (MIMO) systems. By exploiting the angular-domain compressibility of massive MIMO channels, the conceived DL framework can reliably reconstruct the high-dimensional channels from the under-determined measurements. Specifically, we design an end-to-end deep neural network (DNN) architecture composed of dimensionality reduction network and reconstruction network to respectively mimic the pilot signals and channel estimator, which can be acquired by data-driven deep learning. For the dimensionality reduction network, we design a fully-connected layer by compressing the high-dimensional massive MIMO channel vector as input to low-dimensional received measurements, where the weights are regarded as the pilot signals. For the reconstruction network, we design a fully-connected layer followed by multiple cascaded convolutional layers, which will reconstruct the high-dimensional channel as the output. By defining the mean square error between input and output as loss function, we leverage Adam algorithm to train the end-to-end DNN aforementioned with extensive channel samples. In this way, both the pilot signals and channel estimator can be simultaneously obtained. The simulation results demonstrate that the superiority of the proposed solution over state-of-the-art compressive sensing approaches.
Efficient channel state information at transmitter (CSIT) for frequency division duplex (FDD) massive MIMO can facilitate its backward compatibility with existing FDD cellular networks. To date, several CSIT estimation schemes have been proposed for FDD single-cell massive MIMO systems, but they fail to consider inter-cell-interference (ICI) and suffer from downlink pilot contamination in multi-cell scenario. To solve this problem, this paper proposes a compressive sensing (CS)-based CSIT estimation scheme to combat ICI in FDD multi-cell massive MIMO systems. Specifically, angle-domain massive…
This letter studies the pilot contamination (PC) problem for massive multiple-input multiple-output (MIMO) networks with coexisting terrestrial users and unmanned aerial vehicles (UAVs). Due to the strong line-of-sight (LoS) air-to-ground channels between UAVs and base stations (BSs), UAVs usually cause a more severe PC issue as compared to the traditional terrestrial users. To mitigate the PC caused by UAVs, we propose a low-complexity distributed scheme by exploiting the full-dimensional beamforming of massive MIMO BSs and the angle-dependent LoS channels between them and high-altitude UAVs.…
This paper investigates Cell-Free massive MIMO networks, where each access point (AP) is equipped with a hybrid transceiver, reducing the complexity and cost compared to a fully digital transceiver. Asymptotic approximations for the spectral efficiency are derived for uplink and downlink. Capitalizing on these expressions, a max-min problem is formulated to optimize the (i) analog beamformer at the APs and (ii) pilot assignment. Simulations show that the optimization of these variables substantially increases the network performance.
With the large number of antennas and subcarriers the overhead due to pilot transmission for channel estimation can be prohibitive in wideband massive multiple-input multiple-output (MIMO) systems. This can degrade the overall spectral efficiency significantly, and as a result, curtail the potential benefits of massive MIMO. In this paper, we propose a neural network (NN)-based joint pilot design and downlink channel estimation scheme for frequency division duplex (FDD) MIMO orthogonal frequency division multiplex (OFDM) systems. The proposed NN architecture uses fully connected layers for fre…
We propose a strategy for orthogonal downlink pilot assignment in cell-free massive MIMO (multiple-input multiple-output) that exploits knowledge of the channel state information, the channel hardening degree at each user, and the mobility conditions for the users. These elements, properly combined together, are used to define a user pilot utility metric, which measures the user's real need of a downlink pilot for efficient data decoding. The proposed strategy consists in assigning orthogonal downlink pilots only to the users having a pilot utility metric exceeding a predetermined threshold. I…
This letter focuses on the problem of pilot assignment in cell-free massive MIMO systems. Exploiting the well-known Hungarian algorithms, two procedures are proposed, one maximizing the system throughput, and the other one maximizing the fairness across users. The algorithms operate based on the knowledge of large-scale fading coefficients as a proxy for the distances between users in the system and take into account both the uplink and downlink performance. Numerical results show that the proposed pilot assignment algorithms are effective and outperform the many competing alternatives availab…
This paper introduces a hybrid pilot-aided channel estimation technique for mitigating the effect of pilot contamination for the uplink of multi-cell multiuser massive MIMO systems. The proposed hybrid pilot is designed such that it enjoys the complementary advantages between time-multiplexed (TM) pilot and time-superimposed (TS) pilot, and thereby, allows superior solution to the conventional pilot schemes. We mathematically characterize the impact of hybrid pilot on the massive MIMO uplink by deriving a closed-form approximation for the uplink achievable rate. In large-number-of-antennas reg…
A massive multiple-input multiple-output (MIMO) system, which utilizes a large number of base station (BS) antennas to serve a set of users, suffers from pilot contamination due to the inter-cell interference (ICI). In this letter, a graph coloring based pilot allocation (GC-PA) scheme is proposed to mitigate pilot contamination for multi-cell massive MIMO systems. Specifically, by exploiting the large-scale characteristics of fading channels, an interference graph is firstly constructed to describe the potential ICI relationship of all users. Then, with the limited pilot resource, the propose…
Korea University（高丽大学）；Pukyong National University（釜庆国立大学）；Queen’s University（女王大学）
In conventional multi-user multiple-input multiple-output (MU-MIMO) systems with frequency division duplexing (FDD), channel acquisition and precoder optimization processes have been designed separately although they are highly coupled. This paper studies an end-to-end design of downlink MU-MIMO systems which include pilot sequences, limited feedback, and precoding. To address this problem, we propose a novel deep learning (DL) framework which jointly optimizes the feedback information generation at users and the precoder design at a base station (BS). Each procedure in the MU-MIMO systems is …
Massive multiple-input multiple-output (MIMO) are expected to significantly enhance the spectrum efficiency (SE) and energy efficiency (EE) of future cellular systems. Since the performance gain of massive MIMO is fundamentally limited by pilot contamination, pilot reuse design is crucial to achieve reasonable cell throughput and user rate. In this paper, we leverage stochastic geometry to model pilot reuse in massive MIMO systems by introducing a guard region model to match realistic pilot allocation strategies. The uplink signal-to-interference-plus-noise ratio (SINR) distribution is analyti…
Massive MIMO systems, where the base stations are equipped with hundreds of antenna elements, are an attractive way to attain unprecedented spectral efficiency in future wireless networks. In the "classical" massive MIMO setting, the terminals are assumed fully loaded and a main impairment to the performance comes from the inter-cell pilot contamination, i.e., interference from terminals in neighboring cells using the same pilots as in the home cell. However, when the terminals are active intermittently, it is viable to avoid inter-cell contamination by pre-allocation of pilots, while same-cel…
In this paper, we analyze the benefits of including downlink pilots in a cell-free massive MIMO system. We derive an approximate per-user achievable downlink rate for conjugate beamforming processing, which takes into account both uplink and downlink channel estimation errors, and power control. A performance comparison is carried out, in terms of per-user net throughput, considering cell-free massive MIMO operation with and without downlink training, for different network densities. We take also into account the performance improvement provided by max-min fairness power control in the downlin…
The fundamental limitation of massive MIMO technology is pilot contamination effect. This effect occurs during uplink training when terminals use the same orthogonal signals. In this paper, a pilot reuse factor with large scale fading precoding is proposed to mitigate the pilot contamination effect. The pilot reuse factor is designed to assign unique orthogonal signals to the adjacent cells. These unique orthogonal signals are reused only within the cell and hence, intra-pilot contamination is the only concern. Large scale fading precoding is then used to mitigate the intra-pilot contamination…
The focus of this letter is on the reduction of the large pilot overhead in orthogonal frequency division multiplexing (OFDM) based massive multiple-input multiple-output (MIMO) systems. We propose a novel joint channel estimation and equalization technique that requires only one pilot subcarrier, reducing the pilot overhead by orders of magnitude. We take advantage of the coherent bandwidth spanning over multiple subcarrier bands. This allows for a band of subcarriers to be equalized with the channel frequency response (CFR) at a single subcarrier. Subsequently, the detected data symbols are …
In this paper, we consider a constant envelope (CE) pilot-based low-complexity technique for frequency synchronization in multi-user massive MIMO systems. Study of the complexity-performance trade-off shows that this CE-pilot-based technique provides better MSE performance when compared to existing low-complexity high-PAPR pilot-based CFO (carrier frequency offset) estimator. Numerical study of the information rate performance of the TR-MRC receiver in imperfect CSI scenario with this CE-pilot based CFO estimator shows that it is more energy-and-spectrally efficient than existing low-complexit…
We investigate the feasibility of using Massive MIMO to support URLLC in both coherence interval based and 3GPP compliant pilot settings. We consider grant-free uplink transmission with MMSE receiver and adopt 3GPP channel models. In the coherence interval based pilot setting, by extensive system level simulations, we find that using a Massive MIMO base station with 128 antennas and MMSE receiver, URLLC requirements can be achieved in Urban Macro (UMa) Non-Line of Sight (NLoS) with orthogonal pilots and Neyman-Pearson detector. However, in the 3GPP compliant pilot setting, even by using the co…
Reservoir computing (RC) is a special recurrent neural network which consists of a fixed high dimensional feature mapping and trained readout weights. In this paper, we introduce a new RC structure for multiple-input, multiple-output orthogonal frequency-division multiplexing (MIMO-OFDM) symbol detection, namely windowed echo state network (WESN). The theoretical analysis shows that adding buffers in input layers can bring an enhanced short-term memory (STM) to the underlying neural network. Furthermore, a unified training framework is developed for the WESN MIMO-OFDM symbol detector using bot…
A massive multiple-input multiple-output (MIMO) system, which utilizes a large number of antennas at the base station (BS) to serve multiple users, suffers from pilot contamination due to inter-cell interference. A smart pilot assignment (SPA) scheme is proposed in this letter to improve the performance of users with severe pilot contamination. Specifically, by exploiting the large-scale characteristics of fading channels, the BS firstly measures the inter-cell interference of each pilot sequence caused by the users with the same pilot sequence in other adjacent cells. Then, in contrast to the…
Pilot reuse in multi-cell massive multi-input multi-output (MIMO) system is investigated where user groups with different priorities exist. Recent investigation on pilot reuse has revealed that when the ratio of the coherent time interval to the number of users is reasonably high, it is beneficial not to fully reuse pilots from interfering cells. This work finds the optimum pilot assignment strategy that would maximize the weighted sum rate (WSR) given the user groups with different priorities. A closed-form solution for the optimal pilot assignment is derived and is shown to make intuitive se…
We consider the uplink of a cellular massive MIMO network. Since the spectral efficiency of these networks is limited by pilot contamination, the pilot allocation across cells is of paramount importance. However, finding efficient pilot reuse patterns is non-trivial especially in practical asymmetric base station deployments. In this paper, we approach this problem using coalitional game theory. Each cell has its own unique pilots and can form coalitions with other cells to gain access to more pilots. We develop a low-complexity distributed algorithm and prove convergence to an individually st…
Large-scale multiple-input multiple-output (MIMO) with high spectrum and energy efficiency is a very promising key technology for future 5G wireless communications. For large-scale MIMO systems, accurate channel state information (CSI) acquisition is a challenging problem, especially when each user has to distinguish and estimate numerous channels coming from a large number of transmit antennas in the downlink. Unlike the conventional orthogonal pilots whose pilot overhead prohibitively increases with the number of transmit antennas, we propose a spectrum-efficient superimposed pilot design fo…
This paper optimizes the pilot assignment and pilot transmit powers to mitigate pilot contamination in Massive MIMO (multiple-input multiple-output) systems. While prior works have treated pilot assignment as a combinatorial problem, we achieve a more tractable problem formulation by directly optimizing the pilot sequences. To this end, we compute a lower bound on the uplink (UL) spectral efficiency (SE), for Rayleigh fading channels with maximum ratio (MR) detection and arbitrary pilot sequences. We optimize the max-min SE with respect to the pilot sequences and pilot powers, under power budg…
In this paper we consider a constant envelope pilot signal based carrier frequency offset (CFO) estimation in massive multiple-input multiple-output (MIMO) systems. The proposed algorithm performs spatial averaging on the periodogram of the received pilots across the base station (BS) antennas. Our study reveals that the proposed algorithm has complexity only linear in $M$ (the number of BS antennas). Further our analysis and numerical simulations also reveal that with fixed number of users and a fixed pilot length, the minimum required transmit pilot power decreases as $\frac{1}{\sqrt{M}}$ wi…
This paper considers uplink massive MIMO systems with 1-bit analog-to-digital converters (ADCs) and develops a deep-learning based channel estimation framework. In this framework, the prior channel estimation observations and deep neural network models are leveraged to learn the non-trivial mapping from quantized received measurements to channels. For that, we derive the sufficient length and structure of the pilot sequence to guarantee the existence of this mapping function. This leads to the interesting, and \textit{counter-intuitive}, observation that when more antennas are employed by the …
Pilot contamination has been regarded as a main limiting factor of time division duplexing (TDD) massive multiple-input-multiple-output (Massive MIMO) systems, as it will make the signal-to-interference-plus-noise ratio (SINR) saturated. However, how pilot contamination will limit the user capacity of downlink Massive MIMO, i.e., the maximum number of admissible users, has not been addressed. This paper provides an explicit expression of the Massive MIMO user capacity in the pilot-contaminated regime where the number of users is larger than the pilot sequence length. Furthermore, the scheme fo…
This work concerns wireless cellular networks applying massive multiple-input multiple-output (MIMO) technology. In such a system, the base station in a given cell is equipped with a very large number (hundreds or even thousands) of antennas and serves multiple users. Estimation of the channel from the base station to each user is performed at the base station using an uplink pilot sequence. Such a channel estimation procedure suffers from pilot contamination. Orthogonal pilot sequences are used in a given cell but, due to the shortage of orthogonal sequences, the same pilot sequences must be …
This letter shows that optimizing the transmit powers along with optimally designed nonorthogonal pilots can significantly reduce pilot contamination and improve the overall throughput of the uplink multi-cell massive multiple-input multiple-output (MIMO) system as compared to the conventional schemes that use orthogonal pilots. Given the optimized nonorthogonal pilots, power control as a function of the large-scale path-loss can be thought of as a stochastic optimization problem due to the presence of fast fading. This paper advocates a deterministic approach to solve this problem, then furth…
This paper considers the use of NOMA in multiuser MIMO systems in practical scenarios where CSI is acquired through pilot signaling. A new NOMA scheme that uses shared pilots is proposed. Achievable rate analysis is carried out for different pilot signaling schemes including both uplink and downlink pilots. The achievable rate performance of the proposed NOMA scheme with shared pilot within each group is compared with the traditional orthogonal access scheme with orthogonal pilots. Our proposed scheme is a generalization of the orthogonal scheme, and can be reduced to the orthogonal scheme whe…
Since the seminal paper by Marzetta from 2010, Massive MIMO has changed from being a theoretical concept with an infinite number of antennas to a practical technology. The key concepts are adopted in 5G and base stations (BSs) with $M=64$ full-digital transceivers have been commercially deployed in sub-6\,GHz bands. The fast progress was enabled by many solid research contributions of which the vast majority assume spatially uncorrelated channels and signal processing schemes developed for single-cell operation. These assumptions make the performance analysis and optimization of Massive MIMO t…
We consider the pilot assignment problem in large-scale distributed multi-input multi-output (MIMO) networks, where a large number of remote radio head (RRH) antennas are randomly distributed in a wide area, and jointly serve a relatively smaller number of users (UE) coherently. By artificially imposing topological structures on the UE-RRH connectivity, we model the network by a partially-connected interference network, so that the pilot assignment problem can be cast as a topological interference management problem with multiple groupcast messages. Building upon such connection, we formulate …
Massive MIMO uses a large number of antennas to increase the spectral efficiency (SE) through spatial multiplexing of users, which requires accurate channel state information. It is often assumed that regular pilots (RP), where a fraction of the time-frequency resources is reserved for pilots, suffices to provide high SE. However, the SE is limited by the pilot overhead and pilot contamination. An alternative is superimposed pilots (SP) where all resources are used for pilots and data. This removes the pilot overhead and reduces pilot contamination by using longer pilots. However, SP suffers f…
Random access is necessary in crowded scenarios due to the limitation of pilot sequences and the intermittent pattern of device activity. Nowadays, most of the related works are based on independent and identically distributed (i.i.d.) channels. However, massive multiple-input multiple-output (MIMO) channels are not always i.i.d. in realistic outdoor wireless propagation environments. In this paper, a device grouping and pilot set allocation algorithm is proposed for the uplink massive MIMO systems over spatially correlated Rayleigh fading channels. Firstly, devices are divided into multiple g…
Pilot contamination problem in massive MIMO networks operating in time-division duplex (TDD) mode can limit their expected capacity to a great extent. This paper addresses this problem in cosine modulated multitone (CMT) based massive MIMO networks; taking advantage of their so-called blind equalization property. We extend and apply the blind equalization technique from single antenna case to multi-cellular massive MIMO systems and show that it can remove the channel estimation errors (due to pilot contamination effect) without any need for cooperation between different cells or transmission o…
Cell-free Massive multiple-input multiple-output (MIMO) ensures ubiquitous communication at high spectral efficiency (SE) thanks to increased macro-diversity as compared cellular communications. However, system scalability and performance are limited by fronthauling traffic and interference. Unlike conventional precoding schemes that only suppress intra-cell interference, full-pilot zero-forcing (fpZF), introduced in [1], actively suppresses also inter-cell interference, without sharing channel state information (CSI) among the access points (APs). In this study, we derive a new closed-form ex…
A massive MIMO system, represented by a base station with hundreds of antennas, is capable of spatially multiplexing many devices and thus naturally suited to serve dense crowds of wireless devices in emerging applications, such as machine-type communications. Crowd scenarios pose new challenges in the pilot-based acquisition of channel state information and call for pilot access protocols that match the intermittent pattern of device activity. A joint pilot assignment and data transmission protocol based on random access is proposed in this paper for the uplink of a massive MIMO system. The p…
Pilot contamination is known to be one of the main impairments for massive MIMO multi-cell communications. Inspired by the concept of fractional frequency reuse and by recent contributions on pilot reutilization among non-adjacent cells, we propose a new pilot allocation scheme to mitigate this effect. The key idea is to allow users in neighboring cells that are closest to their base stations to reuse the same pilot sequences. Focusing on the uplink, we obtain expressions for the overall spectral efficiency per cell for different linear combining techniques at the base station and use them to …
In this paper, adaptive pilot beam sequence design for channel estimation in large millimeter-wave (mmWave) MIMO systems is considered. By exploiting the sparsity of mmWave MIMO channels with the virtual channel representation and imposing a Markovian random walk assumption on the physical movement of the line-of-sight (LOS) and reflection clusters, it is shown that the sparse channel estimation problem in large mmWave MIMO systems reduces to a sequential detection problem that finds the locations and values of the non-zero-valued bins in a two-dimensional rectangular grid, and the optimal ada…
We propose a novel location-aware pilot assignment scheme to mitigate pilot contamination in massive multiple-input multiple-output (MIMO) networks, where the channels are subjected to Rician fading. Our proposed scheme utilizes the location information of users as the input to conduct pilot assignment in the network. Based on the location information, we first determine the line of sight (LOS) interference between the intended signal and the interfering signal. Our analysis reveals that the LOS interference converges to zero as the number of antennas at the base station (BS) goes to infinity,…
The spectral efficiency (SE) of Massive MIMO (MaMIMO) systems is affected by low quality channel estimates. Rate-Splitting (RS) has recently gained some interest in multiuser multiple antenna systems as an effective means to mitigate the multi-user interference due to imperfect channel state information. This paper investigates the benefits of RS in the downlink of a single-cell MaMIMO system when all the users use the same pilot sequence for channel estimation. Novel expressions for the SE achieved in the downlink by a single-layer RS strategy (that relies on a single successive interference …
Pilot contamination is a limiting factor in multicell massive multiple-input multiple-output (MIMO) systems because it can severely impair channel estimation. Prior works have suggested coordinating pilot design across cells in order to reduce the channel estimation error caused by pilot contamination. In this paper, we propose a method for coordinated pilot design using fractional programming to minimize the weighted mean squared-error (MSE) in channel estimation. In particular, we apply the recently proposed quadratic transform to the MSE expression which allows the effect of pilot contamina…
Distributed or Cell-free (CF) massive Multiple-Input, Multiple-Output (mMIMO), has been recently proposed as an answer to the limitations of the current network-centric systems in providing high-rate ubiquitous transmission. The capability of providing uniform service level makes CF mMIMO a potential technology for beyond-5G and 6G networks. The acquisition of accurate Channel State Information (CSI) is critical for different CF mMIMO operations. Hence, an uplink pilot training phase is used to efficiently estimate transmission channels. The number of available orthogonal pilot signals is limi…
Many real-world scenarios for massive machine-type communication involve sensors monitoring a physical phenomenon. As a consequence, the activity pattern of these sensors will be correlated. In this letter, we study how the correlation of user activities can be exploited to improve detection performance in grant-free random access systems where the users transmit pilot-hopping sequences and the detection is performed based on the received energy. We show that we can expect considerable performance gains by adding regularizers, which take the activity correlation into account, to the non-negati…
In this paper, the impacts of imperfect channel covariance matrix on the spectral efficiency (SE) of cell-free distributed massive multiple-input multiple-output (MIMO) systems are analyzed. We propose to estimate the channel covariance matrix by alternately using the assigned pilots and their phase-shifted pilots in different coherent blocks, which improves the accuracy of channel estimation with imperfect covariance matrix and reduces pilot overhead. Under this scheme, the closed-form expressions of SE with maximum ratio combination (MRC) and zero-forcing (ZF) receivers are derived, which en…
In this paper, we propose a fully-integrated radar and communication system -- named ComSens. We utilize two different pilot sequences (one for uplink and one for downlink) with the condition that they must be uncorrelated to each other. Within such a framework, the signal received from end-user and the back-scattered signal from the desired objects have uncorrelated pilots. Thus, the base-station is able to distinguish data signal from user and back-scattered signal from object. We assume a time division duplex (TDD) framework. The pilot sequences are designed for MIMO channels. We evaluate c…
In this paper, we analyze pilot contamination (PC) attacks on a multi-cell massive multiple-input multiple-output (MIMO) network with correlated pilots. We obtain correlated pilots using a user capacity-achieving pilot sequence design. This design relies on an algorithm which designs correlated pilot sequences based on signal-to-interference-plus-noise ratio (SINR) requirements for all the legitimate users. The pilot design is capable of achieving the SINR requirements for all users even in the presence of PC. However, this design has some intrinsic limitations and vulnerabilities, such as a k…
This letter focuses on the pilot contamination problem in the uplink and downlink of cell-free massive multiple-input multiple-output networks with different degrees of cooperation between access points. The optimum minimum mean square error processing can take advantage of large-scale fading coefficients for canceling the interference of pilot-sharing user-equipments and thus achieves asymptotically unbounded capacity. However, it is computationally demanding and can only be implemented in a fully centralized network. Here, sub-optimal schemes are derived that provide unbounded capacity with …
Pilot contamination, caused by the reuse of pilots among interfering cells, remains as a significant obstacle that limits the performance of massive multi-input multi-output antenna systems. To handle this problem, less aggressive reuse of pilots involving allocation of additional pilots for interfering users is closely examined in this paper. Hierarchical pilot reuse methods are proposed, which effectively mitigate pilot contamination and increase the net throughput of the system. Among the suggested hierarchical pilot reuse schemes, the optimal way of assigning pilots to different users is o…
This paper considers pilot design to mitigate pilot contamination and provide good service for everyone in multi-cell Massive multiple input multiple output (MIMO) systems. Instead of modeling the pilot design as a combinatorial assignment problem, as in prior works, we express the pilot signals using a pilot basis and treat the associated power coefficients as continuous optimization variables. We compute a lower bound on the uplink capacity for Rayleigh fading channels with maximum ratio detection that applies with arbitrary pilot signals. We further formulate the max-min fairness problem un…
This letter proposes anti-jamming strategies based on pilot retransmission for a single user uplink massive MIMO under jamming attack. A jammer is assumed to attack the system both in the training and data transmission phases. We first derive an achievable rate which enables us to analyze the effect of jamming attacks on the system performance. Counter-attack strategies are then proposed to mitigate this effect under two different scenarios: random and deterministic jamming attacks. Numerical results illustrate our analysis and benefit of the proposed schemes.
Wireless links using massive MIMO transceivers are vital for next generation wireless communications networks networks. Precoding in Massive MIMO transmission requires accurate downlink channel state information (CSI). Many recent works have effectively applied deep learning (DL) to jointly train UE-side compression networks for delay domain CSI and a BS-side decoding scheme. Vitally, these works assume that the full delay domain CSI is available at the UE, but in reality, the UE must estimate the delay domain based on a limited number of frequency domain pilots. In this work, we propose a lin…
