Downlink Research Articles

Scaled and nonlinear multi-objective model for Downlink and Uplink exposure in massive MIMO

When designing wireless networks with a large number of wireless broadband devices, it is important to take into account the induced Uplink (UL) and Downlink (DL) exposure from base station broadcasting. This work focuses on the reduction of power consumption, low downlink and uplink electromagnetic exposure, and the optimization of locations and power levels of large Multiple Input–Multiple Output-Long Term Evolution base stations (MIMO-LTE). Additionally, it anticipates achieving maximum user coverage. In order to handle the power consumption and Electro Magnetic Field (EMF) exposure, a Nonlinear and Scaled Weight objective model (NLSW) is defined (DL and UL exposure). An enhanced Particle Swarm Optimization (PSO) technique is employed to resolve this optimization issue. Finally, DL exposure, UL exposure, and power performance of a NLSW are validated compared to the traditional linear model. Increased antenna leads to a 25% reduction in DL dosage. The minimum BS deployed in the area with the number of antenna elements until it reaches the ideal value is related to the UL exposure maximization.

Improving the Sustainability of Confirmed Traffic in LoRaWANs Through an Adaptive Congestion Scheme

The scalability of long-range wide area networks (LoRaWANs) is known to be very sensitive to the presence of traffic from gateways (GWs) to end devices (downlink (DL) traffic). The protocol supports confirmed traffic, for which DL traffic is generated in the form of acknowledgments (ACKs). Research has shown that even a limited number of ACKs quickly cause network congestion, negatively impacting scalability. This article introduces a mechanism, the adaptive congestion scheme (ACS), which aims to monitor the congestion caused by DL traffic and take steps to reduce it. Currently, the ACS supports one counteraction in the form of a newly developed algorithm called groupedPackets (also introduced in this article). This algorithm reduces the number of sent confirmed packets by requesting that confirmed nodes (nodes that only send confirmed traffic) aggregate their application packets. Simulations showed that this algorithm improved the successful delivery of both unconfirmed traffic and confirmed traffic. When traffic volumes are low, the algorithm has a minimal impact, but at high network packet arrival rates (higher than 0.1 pkt/s), the successful delivery of especially confirmed traffic increased significantly.

Statistical Beamforming for Multi-Set Space–Time Shift-Keying-Based Full-Duplex Millimeter Wave Communications

Full-duplex (FD) communication has been shown to provide an increased achievable rate, while millimeter wave (mmWave) communications benefit from a large available bandwidth that further improves the achievable rate. On the other hand, the concept of multi-set space-time shift keying (MS-STSK) has been proposed to provide a flexible design trade-off between throughput and performance. Hence, in this work, we consider the design of an FD-aided MS-STSK transceiver for millimeter wave communications. However, a major challenge is that channel reciprocity is not valid in mmWave communications due to shorter channel coherence time. Thus, the uplink (UL) pilots cannot be utilized to estimate the downlink (DL) channel. To overcome this challenge, we propose a beamforming technique based on channel statistics without assuming channel reciprocity. For this purpose, a closed-form expression for the outage probability of the system is derived by employing the characterization of the ratio of the Indefinite Quadratic Form (IQF). The derived analytical expression is then utilized to design optimum beamforming weights using the Sequential Quadratic Programming (SQP)-based heuristic method. Moreover, an Iterative Statistical Method (ISM) of joint transmit and receive beamforming algorithm is also developed by utilizing Principle Eigenvector (PE) and Generalized Rayleigh Quotient (G-RQ) optimization techniques. Finally, we verify our simulation results with the theoretical analysis.

STAR-RIS Assisted Downlink Active and Uplink Backscatter Communications with NOMA

A simultaneously transmitting and reflecting reconfigurable intelligent surface (STAR-RIS) assisted downlink (DL) active and uplink (UL) backscatter communication (BackCom) framework is proposed. More particularly, a full-duplex (FD) base station (BS) communicates with the DL users via the STAR-RIS's transmission link, while exciting and receiving the information from the UL BackCom devices with the aid of the STAR-RIS's reflection link. Non-orthogonal multiple access (NOMA) is exploited in both DL and UL communications for improving the spectrum efficiency. The system weighted sum rate maximization problem is formulated for jointly optimizing the FD BS active receive and transmit beamforming, the STAR-RIS passive beamforming, and the DL NOMA decoding orders, subject to the DL user's individual rate constraint. To tackle this challenging non-convex problem, we propose an alternating optimization (AO) based algorithm for the joint active and passive beamforming design with a given DL NOMA decoding order. To address the potential high computational complexity required for exhaustive searching all the NOMA decoding orders, an efficient NOMA user ordering scheme is further developed. Finally, numerical results demonstrate that: i) compared with the baseline schemes employing conventional RISs or space division multiple access, the proposed scheme achieves higher performance gains; and ii) higher UL rate gain is obtained at a cost of DL performance degradation, as a remedy, a more flexible performance tradeoff can be achieved by introducing the STAR-RIS.

D2D Assisted Multi-Antenna Coded Caching

A device-to-device (D2D) aided multi-antenna coded caching scheme is proposed to improve the average delivery rate and reduce the downlink (DL) beamforming complexity. Novel beamforming and resource allocation schemes are proposed where local data exchange among nearby users is exploited. The transmission is split into two phases: local D2D content exchange and DL transmission. In the D2D phase, subsets of users are selected to share content with the adjacent users directly. In this regard, a low complexity D2D mode selection algorithm is proposed to find the appropriate set of users for the D2D phase with comparable performance to the optimal exhaustive search. During the DL phase, the base station multicasts the remaining data requested by all the users. We identify scenarios and conditions where D2D transmission can reduce the delivery time. Furthermore, we demonstrate how adding the new D2D phase to the DL-only scenario can significantly reduce the beamformer design complexity in the DL phase. The results further highlight that by partly delivering requested data in the D2D phase, the transmission rate can be boosted due to more efficient use of resources during the subsequent DL phase. As a result, the overall content delivery performance is greatly enhanced, especially in the finite signal-to-noise (SNR) regime.

Modified User Grouping and Hybrid Precoding for Information Decoding and Energy Harvesting in Hardware Impaired Point-To-Point MM-Wave Massive MIMO NOMA

The fifth generation (5G) and beyond 5G race covers both spectral-efficient and energy-efficient mechanisms such as simultaneous wireless information decoding and energy harvesting (SWIDEH). Structured as full or sub-connection of hybrid-precoded mm-wave massive multiple-input multiple-output non-orthogonal multiple access (NOMA) systems. However, the more practical hardware-impaired (HI) functionality yet to be considered for point-to-point (p-to-p) MIMO is conceived from an existing system. A hardware impairment-based power splitting is proposed for energy harvesting. The energy of the HI signal is harnessed through the joint optimization of power allocation (PA) for information decoding (ID) and the power splitting (PS) factor for energy harvesting (EH) using zero-forcing (ZF) precoding and minimum mean square error (MMSE) downlink (DL) detection. Based on the simulation results, an adaptive cluster head selection (CHS) criterion is proposed for analog precoding to mitigate intracluster interferences at a high signal-to-noise ratio (SINR). A successive interference cancellation (SIC) is carried out to enable dynamic channel overhead estimation and user signal detection. An investigation is done by simulating the system performance at varied numbers of users, the number of radio-frequency (RF) chains, and channel characteristics for modelling the user group threshold coupled with channel size reduction via an antenna selection scheme. Observing the execution time and some graphical plots shows that the spectral and energy efficiency can be improved by a random (R) or maximum norm average (MNA) channel vector formation from each user’s channel matrix combined with the best adaptive correlation threshold during CHS and a regularized ZF (RZF) precoder.

Fairness Oriented H-NOMA Devices Association and Pairing in HCN Slicing Using Cooperation Games

Device association (DA) and pairing (DP) are presented in this letter to evaluate the fairness of different services between enhanced mobile broadband devices (eMBBDs) and ultra-reliability low latency communications devices (uRLLCDs) in RAN-slicing, which has emerged as a viable technique for enhancing total network throughput in heterogeneous cellular networks (HCNs) design. To optimize the eMBBDs' downlink (DL) sum rate while fulfilling the provisions of the uRLLC traffic. A cooperative Nash bargaining solution (NBS) is formulated to depict the association method. First, base stations (BSs) create random pairings between heterogeneous non-orthogonal multi-access (H-NOMA) devices. The BSs are classified into coalitions through the Hungarian approach. So, a two-band partition algorithm is evolved for the two BSs in each coalition to negotiate their allocated devices to improve the NBS utility. A multiplayer bargaining approach is constructed using this algorithm and the Hungarian technique. After finishing the DA process, we study the cooperative matching algorithm to optimize the pairing problem between devices' slices. Simulation results demonstrate that comparing the proposed approach to other schemes can achieve a significant DL rate distribution for eMBBDs, device-side latency for uRLLCDs, and fairness improvements.

Further Research on Frequency Allocation (19-Cell System) Method based on IFR and FFR

Many of the most advanced technology has a basic need for efficient telecommunication. In order to achieve this goal, the team should allocate those frequency channels in an intelligent way so that the interference can be reduced to the maximum extent. Here the team introduced a new method based on IFR3&IFR1 (Integer frequency reuse) in a 19-cell network, but also apply the FFR (fractional frequency reuse) method to reduce the interference ulteriorly. In the pure IFR situation, the integer frequency reuse factor and the cellular network specification collectively decide the network capacity. While in FFR only a fraction of the whole bandwidth is used by the users in the edge. By contrast, the users near the BS can make use of the total bandwidth. The cell is divided into an outer and an inner part in this effective way. Fractional Frequency Reuse (FFR) and its derivative method are accepted widely in the downlink (DL) inter-cell interference coordination(ICIC) schemes. The team also optimized the FFR method by measuring the distance in a more precise way. The team utilized Matlab to make a simulation of the system applying the new method and come to a couple of reasonable conclusions by comparing the FFR+IFR3 with FFR+IFR3. FFR+IFR3 has a better performance against FFR+IFR1 in a system whose distance between each cell is with more accuracy. While the average number of users per cell and transmission power for cell edge have little impact on average capacity. When the SNR increases, the network capacity starts steep but later flattens. Our method is more intelligent and can minish interference efficiently.

Performance analysis of dynamic ordered NOMA system

Non-orthogonal multiple access (NOMA) has emerged as a key enabling technology for the fifth generation (5G) and beyond networks. NOMA supports massive mobile connectivity, increases spectral efficiency, and ensures user fairness by providing access to various users to share common wireless resources. In this work, the analysis of sum-rate and outage probability (OP) has been carried out in the case of a downlink (DL) dynamic ordered NOMA (D-NOMA) system. Sum-rate of the system has been maximized using Karush-Kuhn-Tucker (KKT) technique. Expressions of OP are obtained over the Rayleigh fading channel. Finally, simulations are done to confirm the expressions obtained for OP and sum-rate. Also, a sum-rate comparison between the D-NOMA system and the fixed NOMA (F-NOMA) system has been done.

3GPP Release-17 Physical Layer Enhancements for LTE-M and NB-IoT

The 3rd Generation Partnership Project (3GPP) introduced Long-Term Evolution (LTE) for Machine-Type Communications (LTE-M) and Narrowband Internet of Things (NB-IoT) in Release 13 (Rel-13) as part of the fourth generation LTE. Both technologies provide wide-area connectivity to “things” that benefit from being connected including sensors, machines, actuators, and so on. LTE-M and NB-IoT continued their evolution across successive 3GPP releases providing higher data rates, power saving features, coexistence with the fifth generation New Radio (NR), and so on. In Release-17 (Rel-17), 16-quadrature amplitude modulation (16-QAM) in uplink (UL) and downlink (DL) for NB-IoT, as well as the support of up to 14 hybrid automatic repeat request (HARQ) processes and a new maximum DL transporting block size (TBS) for half duplex frequency-division duplexing (HD-FDD) LTE-M devices were standardized. This article provides an overview of the Rel-17 physical layer enhancements according to the 3GPP specifications, including descriptions of their technical components, qualitative gains, and performance evaluations. For NB-IoT, 16-QAM in DL nearly doubles the peak data rate using a larger maximum DL TBS, whereas 16-QAM in UL allows transmitting the largest TBS available for quadrature phase shift keying using half of the resources in the time domain. For LTE-M, for HD-FDD Category M1 (Cat-M1) UEs, the 14 HARQ processes feature adds full support for handling the presence of invalid subframes and increases the DL peak data rate by 20 percent, whereas the introduction of a larger maximum DL TBS further increases the DL peak data rate by 73.6 percent.

Superimposed Pilot Transmission in Cell-Free Massive MIMO With Non-Ideal RF Responses

In this paper, the performance of cell-free massive multiple-input multiple-output (CF-mMIMO) systems under the transceiver non-ideal radio-frequency responses (NI-RF-RPs) that rely on the superimposed pilot (SP) and regular pilot (RP) transmission protocols is investigated. Specifically, the transceiver NI-RF-RPs encapsulate the non-ideal amplitude responses (NI-A-RPs) and non-ideal phase responses (NI-P-RPs) at both access points (APs) and users (UEs). By virtue of a generic RF-RP model, rigorous closed-form expressions of uplink (UL) and downlink (DL) achievable spectral efficiencies (SEs) with different NI-RF-RPs and pilot transmission protocols are respectively derived, which enable us to quantify the impact of the key system parameters, such as the transceiver amplitude (and phase) response variances and the transceiver reciprocity. Numerical results demonstrate that the SP protocol is superior to the RP protocol in terms of the UL and DL SEs, regardless of the presence of the NI-RF-RPs. Besides, the NI-A-RPs have negative effect on both UL and DL SEs, and the DL SE is immune to the transceiver amplitude non-reciprocity. Moreover, from the perspective of the NI-P-RPs, it is shown that the DL SE is only sensitive to the AP NI-P-RPs and whether the AP phase is reciprocal or not will significantly disturb the effect of the NI-P-RPs on the DL SE.

Full-Duplex Massive Multiple-Input, Multiple-Output Architectures: Recent Advances, Applications, and Future Directions

The increasingly demanding objectives for next-generation wireless communications have spurred recent research activities on multiantenna transceiver hardware architectures and relevant intelligent communication schemes. Among them belong full-duplex (FD) multiple-input, multiple-output (MIMO) architectures, which offer the potential for simultaneous uplink (UL) and downlink (DL) operations in the entire frequency band. However, as the number of antenna elements increases, the interference signal leaking from the transmitter (Tx) of the FD radio to its receiver (Rx) becomes more severe. In this article, we present a unified FD massive MIMO architecture comprising analog and digital transmit and receive beamforming (BF) as well as analog and digital self-interference (SI) cancellation, which can be jointly optimized for various performance objectives and complexity requirements. The performance evaluation results for applications of the proposed architecture to fully digital and hybrid analog and digital-BF operations using recent algorithmic designs as well as simultaneous communication of data and control (SCDC) signals are presented. It is shown that the proposed architecture, for both small and large numbers of antennas, enables improved spectral-efficient FD communications with fewer analog-cancellation elements compared to various benchmark schemes. The article concludes with a list of open challenges and research directions for future FD massive MIMO communication systems and their promising applications.

Joint Power and Time Allocation in Hybrid NoMA/OMA IoT Networks for Two-Way Communications.

This article investigates two-way communications between an access point (AP) and multiple terminals in low-cost Internet of Things (IoT) networks. The main issues considered are the asymmetric transmission traffic on the uplink (UL) and downlink (DL), and the unbalanced receivers processing capability at the AP and the terminals. As a solution, a hybrid non-orthogonal multiple access/orthogonal multiple access (NoMA/OMA) scheme together with a joint power and time allocation method is proposed to address these issues. For the system design, we formulated the optimization problem with the aim of minimizing the system power and satisfying the UL and DL transmission rate constraints. Due to the coupling of power and time variables in the objective function and the multi-user interference (MUI) in the UL transmission rate constraints, the formulated problem is shown to be non-linear and non-convex and thus is hard to solve. To obtain a numerical, efficient solution, the original problem is first reformulated to be a convex one relying on the successive convex approximation (SCA) method, and then a numerical efficient solution is thus obtained by using an iterative routine. The proposed transmission scheme is shown to be not only physically feasible but also power-efficient.

Fairness-based user association and resource blocks allocation in satellite–terrestrial integrated networks

To meet the futuristic communications needs, a satellite–terrestrial integrated network (STIN) has been proposed and is a strong contender amongst emerging architectures. In our STIN model, we have considered a satellite-based base station (BS), dovetailed with a terrestrial N-tier heterogeneous network (HetNets). Our work considers jointly admission control of user equipment (UE), power allocation , fairness-based user association (UA), and fair spectrum resource allocation to UEs in STIN. With throughput maximization as an objective, considering such an environment, has not been investigated in the past. The formulated problem is a mixed integer non-linear programming (MINLP) problem that is Non-deterministic Polynomial-time Hard (NP-hard) and to achieve an optimal solution, it requires an exhaustive search. But, the computational load of exhaustive search increases exponentially as the number of UEs increases. Therefore, to obtain a near-optimal solution having low computational load an outer approximation algorithm (OAA) is proposed. To evaluate the proposed algorithm, extensive simulation work has been performed. The effectiveness of the proposed approach is verified by the results in terms of fairness in UA, fairness in resource block (RB) allocation, and throughput in the downlink (DL).

Federated Learning in Massive MIMO 6G Networks: Convergence Analysis and Communication-Efficient Design

In federated learning (FL), model weights must be updated at local users and the base station (BS). These weights are subjected to uplink (UL) and downlink (DL) transmission errors due to the limited reliability of wireless channels. In this paper, we investigate the impact of imperfections in both UL and DL links. First, for a multi-user massive multi-input-multi-output (mMIMO) 6G network, employing zero-forcing (ZF) and minimum mean-squared-error (MMSE) schemes, we analyze the estimation errors of weights for each round. A tighter convergence bound on the modelling error for the communication efficient FL algorithm is derived of the order of <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$\mathcal{O}\left(T^{-1}\sigma_{z}^{2}\right)$</tex-math></inline-formula> , where… <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$\sigma_z^{2}$</tex-math></inline-formula> denotes the variance of overall communication error including the quantization noise. The analysis shows that the reliability of DL links is more critical than that of UL links; and the transmit power can be varied in training process to reduce energy consumption. We also vary the number of local training steps, average codeword length after quantization and scheduling policy to improve the communication efficiency. Simulations with image classification problems on MNIST, EMNIST and FMNIST datasets verify the derived bound and are useful to infer the minimum SNR required for successful convergence of the FL algorithm.

Secrecy Throughput Maximization for IRS-Aided MIMO Wireless Powered Communication Networks

In this paper, we consider deploying an intelligent reflecting surface (IRS) to enhance the downlink (DL) energy transfer and uplink (UL) information transmission efficiency for secure multiple-input multiple-output (MIMO) wireless powered communication networks (WPCNs). We aim to maximize the secrecy throughput of all users by jointly optimizing the DL/UL time allocation, the energy transmit covariance matrix of hybrid access point (AP), the information transmit beamforming matrix of users and the phase shifts of IRS in DL/UL, subject to constraints of energy/information transmit power at the hybrid AP/users and that of unit-modulus IRS phase shifts for DL/UL. To tackle the non-convex problem, we first transform the original problem into an equivalent form based on the mean-square error (MSE) method given time allocation, and then apply the alternating algorithm to update the optimization variables iteratively. Specifically, the energy covariance matrix and the information beamforming matrix are obtained based on the dual subgradient method. For the IRS phase shifts, we investigate two IRS beamforming reflection setups, namely different DL/UL IRS beamforming and identical DL/UL IRS beamforming. For the former case, the second-order cone programming technique and the Majorization-Minimization algorithm/element by element iterative algorithm are applied to obtain the DL and UL IRS phase shifts, respectively. For the latter case, the IRS phase shifts are obtained by the successive convex approximation technique. To further reduce the computational complexity of the single-user system, we derive the closed-form solutions of IRS phase shifts in each iteration for the two different reflection setups. Simulation results show that all the proposed algorithms can greatly improve the secrecy throughput compared to the conventional system without IRS.

Joint Analog and Digital Transceiver Design for Wideband Full Duplex MIMO Systems

In this paper, we propose a wideband Full Duplex (FD) Multiple-Input Multiple-Output (MIMO) communication system comprising of an FD MIMO node simultaneously communicating with two multi-antenna UpLink (UL) and DownLink (DL) nodes utilizing the same time and frequency resources. To suppress the strong Self-Interference (SI) signal due to simultaneous transmission and reception in FD MIMO systems, we propose a joint design of Analog and Digital (A/D) cancellation as well as transmit and receive beamforming capitalizing on baseband Orthogonal Frequency-Division Multiplexing (OFDM) signal modeling. Considering practical transmitter impairments, we present a multi-tap wideband analog canceller architecture whose number of taps does not scale with the number of transceiver antennas and multipath SI components. We also propose a novel adaptive digital cancellation based on truncated singular value decomposition that reduces the residual SI signal estimation parameters. To maximize the FD sum rate, a joint optimization framework is presented for A/D cancellation and digital beamforming. Finally, our extensive waveform simulation results demonstrate that the proposed wideband FD MIMO design exhibits higher SI cancellation capability with reduced complexity compared to existing cancellation techniques, resulting in improved achievable rate performance.

Blind RIS Aided Ordered NOMA: Design, Probability of Outage Analysis and Transmit Power Optimization

Non-orthogonal multiple access (NOMA) has been widely acclaimed as a promising solution to enhance spectral efficiency, increase user fairness, and scale up the number of users in wireless networks by enabling multiple users to share the symmetrical wireless resources. This work is concerned with the development and implementation of blind reconfigurable intelligent surface (RIS)-aided ordered NOMA (ONOMA) for smart reflector (SR) and access point (AP) configurations. For the RIS-SR-ONOMA and RIS-AP-ONOMA configurations, the closed-form probability of outage expressions is derived, and their performance is reported for distinct values of passive reflector elements. Through optimal power allocation, the downlink (DL) sum capacity is maximized. RIS-aided ONOMA reduces outage rates and increases sum capacity over the traditional ONOMA system. It is discovered that the RIS-aided ONOMA system increases the sum capacity by ≈33% at 20 dB signal-to-noise ratio (SNR) for 32 passive reflector elements. The addition of passive reflector elements and symmetrical allocation among users improves the performance of RIS-SR-ONOMA and RIS-AP-ONOMA in terms of outage probability, sum capacity, and probability of error. The proposed work can be employed in applications such as vehicular ad hoc networks, where obtaining precise channel information is difficult due to the rapid mobility of the vehicles.

PCA-Based Adaptive Training-Feedback Scheme in Time-Varying FDD Massive MIMO Systems

For massive multiple-input multiple-output (MIMO) systems, the real-time channel state information (CSI) acquisition is crucial but difficult in fast time-varying scenarios, especially for downlink (DL) channels in frequency division duplex (FDD) systems. This paper proposes an adaptive training-feedback scheme to estimate the CSI of DL channels. Specifically, first, base station (BS) determines a subspace containing uplink (UL) channel and an orthogonal normal basis of this subspace by using received signals in UL channel and the principle component analysis (PCA) technique. Second, by using the spatial reciprocity, it is found that the obtained subspace above also contains the DL channel vector. Thus, regarding the basis as pilots, the BS transmits pilots to mobile user (MU), and the user estimates received signals, feeds back them to the BS. Finally, according to information of the feedback, the BS can construct the DL channel vector. In this scheme, the pilots are adaptive to the change of the UL channel. Furthermore, the times of training is the dimension of the subspace, and feedback overhead is the coefficients of linear combination of DL channel vector under the basis only. Thus, cost of training and feedback can be greatly reduced. The simulation results show that the performance of the proposed scheme can approach the optimal scheme with very few training times and feedback overhead at high speed.

Quantization-Aided Secrecy: FD C-RAN Communications With Untrusted Radios

In this work, we study a full-duplex (FD) cloud radio access network (C-RAN) from the aspects of infrastructure sharing and information secrecy, where the central unit utilizes FD remote radio units (RU)s belonging to the same operator, i.e., the trusted RUs, as well as the RUs belonging to other operators or private owners, i.e., the untrusted RUs. Furthermore, the communication takes place in the presence of untrusted external receivers, i.e., eavesdropper nodes. The communicated uplink (UL) and downlink (DL) waveforms are quantized in order to comply with the limited capacity of the fronthaul links. In order to provide information secrecy, we propose a novel utilization of the quantization noise shaping in the DL, such that it is simultaneously used to comply with the limited capacity of the fronthaul links, as well as to degrade decoding capability of the individual eavesdropper and the untrusted RUs for both the UL and DL communications. In this regard, expressions describing the achievable secrecy rates are obtained. An optimization problem for jointly designing the DL and UL quantization and precoding strategies are then formulated, with the purpose of maximizing the overall system weighted sum secrecy rate. Due to the intractability of the formulated problem, an iterative solution is proposed, following the successive inner approximation and semi-definite relaxation frameworks, with convergence to a stationary point. Numerical evaluations indicate a promising gain of the proposed approaches for providing information secrecy against the untrusted infrastructure nodes and/or external eavesdroppers in the context of FD C-RAN communications.