Full-duplex Base Station Research Articles

Proximal Policy Optimization for RIS-Assisted Full Duplex 6G-V2X Communications

In this work, we consider a novel reconfigurable intelligent surface (RIS)-assisted full-duplex (FD) sixth generation (6G)-vehicle-to-everything (V2X) communication network having a FD base station (BS) simultaneously communicating with a uplink (UL) and a downlink (DL) mobile vehicles with the aide of two RISs, one for each link. We provide an analytical framework to investigate the performance of this network and, consequently, formulate an optimization problem to jointly optimize the phase shift matrices at both the RISs that maximize the achievable sum-rate. Thereafter, due to the non-convex nature of the problem, we propose a low complexity proximal policy optimization (PPO)-based deep reinforcement learning (DRL) algorithm that solves the problem in continuous action spaces by reducing the overall training overhead and provides optimum values of phase-shift matrix at each RIS. Further, we extend the analysis considering multiple transmit and receive antennas at the BS that simultaneously serves multiple UL and DL vehicles. We present exhaustive simulations-based graphical results to validate the effectiveness and accuracy of the proposed algorithm compared to deep deterministic policy gradient (DDPG) and successive refinement (SR)-based solutions. Accordingly, we demonstrate the dominance of the considered FD system over its half-duplex (HD) counterpart. We also discuss the impact of the number of elements at each RIS, each vehicle's velocity and their distance from the RIS and the BS on the performance of the respective links. Moreover, we also highlight the impact of imperfect self-interference cancellation and discuss the trade-off between the UL and DL performances due to this imperfection. Additionally, it is shown that the proposed algorithm is approximately <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$10 \times$</tex-math></inline-formula> and <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$ 40 \times$</tex-math></inline-formula> faster than DDPG and SR, respectively. Finally, for the multiple vehicle case, we demonstrate the effect of co-channel interference on the DL rate and the impact of RIS elements, the number of UL and DL vehicles on the system performance.

Reconfigurable Intelligent Surfaces Between the Reality and Imagination

One interesting idea that could improve wireless communication systems is reconfigurable intelligent surfaces or RIS. To control the spread of wireless signals, RIS uses a plethora of tiny, inexpensive, and customizable reflecting devices. Signal strength, energy consumption, spectrum efficiency, and adaptability to changes in the wireless environment can all be improved by altering the phase shift of the reflecting elements. This is how RIS works. 5G and beyond, the IoT, and smart cities are just a few of the many potential uses for RIS. More study is required before this technology can reach its full potential since it is still in its infancy. Still, RIS is going to be big in the next generation of wireless networks. A great deal of excitement has enveloped the whole 6G development industry. There has been no shortage of grandiose and frequently unfounded assertions that, in reality, the creation of a full-duplex 5G technology that can introduce new services is just around the corner, even though self-interference cancellation schemes for full-duplex communications and the difficulties of building full-duplex base stations have long been known.

A novel resource allocation scheme for full-duplex NOMA systems with power splitting-based SWIPT

This paper introduces novel resource allocation (RA) algorithms for optimizing wireless network performance, focusing on a full-duplex (FD) base station (BS) employing non-orthogonal multiple access (NOMA) technology. Motivated by the intriguing trade-off introduced by the simultaneous wireless information and power transfer (SWIPT) scheme, in which achievable data rates are sacrificed to enhance harvested energy, this study aims to quantify the delicate equilibrium between two vital aspects meticulously: the overall achievable data rate facilitated by NOMA and FD technologies and the energy harvested via the SWIPT approach. Specifically, our focus is on jointly optimizing the enhancement of both data rate and harvested energy for downlink (DL) users where a multi-objective optimization approach is developed in the proposed RA algorithm to study the existing trade-off between these conflicting objective functions. This problem optimizes the power allocation for both the BS and the users, allocating subcarriers, and optimizing the power splitting factor for SWIPT scheme. We developed efficient iterative solutions for the intended RA problems because they involve complex mixed-integer nonlinear optimization challenges that are generally difficult to solve. The effectiveness of the proposed RA framework is demonstrated using simulation results. These results investigate whether FD MC-NOMA systems, enabled by the proposed RA algorithms, provide a significant increase in system throughput compared to both conventional half-duplex (HD) multicarrier orthogonal multiple access (MC-OMA) systems and HD MC-NOMA systems, as well as other baseline methods. The results also demonstrate that our proposed scheme allows for a greater power harvest than the OMA-FD configuration and other baseline schemes.

Joint Beamforming and Phase Shifts Design for RIS-Aided Multi-User Full-Duplex Systems in Smart Cities.

Full-duplex (FD) and reconfigurable intelligent surface (RIS) are potential technologies for achieving wireless communication effectively. Therefore, in theory, the RIS-aided FD system is supposed to enhance spectral efficiency significantly for the ubiquitous Internet of Things devices in smart cities. However, this technology additionally induces the loop-interference (LI) of RIS on the residual self-interference (SI) of the FD base station, especially in complicated urban outdoor environments, which will somewhat counterbalance the performance benefit. Inspired by this, we first establish an objective and constraints considering the residual SI and LI in two typical urban outdoor scenarios. Then, we decompose the original problem into two subproblems according to the variable types and jointly design the beamforming matrices and phase shifts vector methods. Specifically, we propose a successive convex approximation algorithm and a soft actor-critic deep reinforcement learning-related scheme to solve the subproblems alternately. To prove the effectiveness of our proposal, we introduce benchmarks of RIS phase shifts design for comparison. The simulation results show that the performance of the low-complexity proposed algorithm is only slightly lower than the exhaustive search method and outperforms the fixed-point iteration scheme. Moreover, the proposal in scenario two is more outstanding, demonstrating the application predominance in urban outdoor environments.

RIS-Assisted Self-Interference Mitigation for In-Band Full-Duplex Transceivers

The wireless in-band full-duplex (IBFD) technology can in theory double the system capacity over the conventional frequency division duplex (FDD) or time-division duplex (TDD) alternatives. But the strong self-interference of the IBFD can cause excessive quantization noise at the output of the analog-to-digital converters (ADCs), which hampers its real implementation. Fortunately, the reconfigurable intelligent surface (RIS) can reconfigure the wireless channels by dynamically adjusting the reflection coefficients, which makes it a promising solution to self-interference mitigation (SIM) for the IBFD system. This paper considers a RIS-assisted IBFD (RAIBFD) system where a full-duplex base station (BS), assisted by a co-located RIS, receives and transmits signals on the same frequency band simultaneously. We propose to jointly design the DL precoding matrix and the RIS coefficients to mitigate the strong self-interference before the ADCs of finite bit resolutions. To gauge the performance of the proposed RAIBFD system, we also consider an idealistic RIS-assisted IBFD (I-RAIBFD) system with ADCs of infinite bit resolutions and RIS-assisted FDD (RAFDD) system, and take them as performance benchmarks. The effectiveness of the proposed RAIBFD system is verified by simulation studies, even if the phases of the RIS have only finite resolutions.

In band full duplex (IBFD) technology for next generation wireless networks: A survey in cellular networks

Next-Generation (NextG) wireless communication networks with their widespread applications require high data rates, seamless connectivity and high quality of service (QoS). To cope up with an unprecedented rise of data hungry applications, users demand more spectral resources imposing a limitation on available wireless spectrum. One of the potential solutions to address the spectrum scarce issue is to incorporate in band full duplex (IBFD) or full duplex (FD) paradigm in next generation networks including 5G new radio (NR). Recently, FD has gained the research interest in cellular networks for its potential to double the wireless link capacity and enhancing spectral efficiency (SE). In half duplex (HD) cellular networks, base stations (BSs) can either perform uplink (UL) or downlink (DL) transmission at a particular time instant leading to reduced throughput levels. Due to the advancement in the self interference reduction (SIR) techniques, full duplex base stations (FD-BSs) can be employed to allow simultaneous UL and DL transmissions at the same time-frequency resources as compared to its HD counterpart. It ideally achieves twice the throughput without any additional complexity at user-equipment(UE). This paper covers a detailed survey on FD cellular networks. A series of SIR approaches, UE-UE mitigation techniques are summarized. Various existing MAC protocols and antenna architectures for FD cellular networks are outlined. An overview of security aspects for FD in cellular networks is also presented. Lastly, various open issues and possible research directions are brought up for FD cellular networks.

Energy efficiency maximisation for STAR‐RIS assisted full‐duplex communications

AbstractReconfigurable intelligent surface (RIS) has emerged as a promising technique for enhancing the performance of wireless networks. However, the traditional reflecting‐only RIS requires that the transmitter and receiver ought to be on the same side of the RIS, limiting the flexibility of RIS deployment. To overcome this drawback, a new simultaneous transmission and reflection reconfigurable intelligent surface (STAR‐RIS) has been proposed. Different from STAR‐RIS assisted half‐duplex systems in the existing literature, this work investigates a novel STAR‐RIS aided full‐duplex (FD) communication system. An FD base station (BS) communicates with an uplink (UL) user and a downlink user simultaneously over the same time‐frequency dimension assisted by a STAR‐RIS. The authors aim to maximise the energy efficiency by jointly optimising the transmit power of the BS and the UL user and the passive beamforming at the STAR‐RIS. The authors decouple the non‐convex problem into two subproblems and optimise them iteratively. The Dinkelbach's method is used to solve the power optimisation subproblem, whereas the penalty‐based method and successive convex approximation are applied to design the passive beamforming. The convergence and complexity of the proposed algorithm are also analysed. The simulation results demonstrate the superior performance of the proposed scheme compared with other baseline schemes.

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.

Covertness and Secrecy Study in Untrusted Relay-Assisted D2D Networks

This article investigates the covertness and secrecy of wireless communications in an untrusted relay-assisted device-to-device (D2D) network consisting of a full-duplex base station (BS), a user equipment (UE), and an untrusted relay <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">${R}$ </tex-math></inline-formula> . For the covertness, we attempt to prevent Willie from detecting the very existence of communications via a D2D link from UE to R and cellular link from R to BS, while for the secrecy, we aim to prevent the untrusted relay from eavesdropping the UE message. To explore the fundamental covertness and secrecy in such a network, we first provide theoretical modelings for the average minimum detection error rate of Willie, and the average covert/secrecy rate from UE to BS under the underlay and overlay modes, respectively. Based on these models, th we further explore the optimal power control at UE, R, and BS to achieve the average covert rate maximization (MCR) for UE with the constraints of covertness and security requirements under the underlay mode. We also identify the optimal transmit powers and the optimal spectrum partition factor for MCR under the overlay mode. Finally, the exhaust searching method is adopted to solve the MCR problems, and extensive numerical and simulation results are presented to validate our theoretical analysis and to illustrate the average covert rate and secrecy rate of UE under various scenarios.

Joint Resource Allocation and Power Control for Full-Duplex V2I Communication in High-Density Vehicular Network

It is significant to satisfy the diverse Vehicle-to-everything (V2X) Quality of Service (QoS) demands for the high-density vehicular network. The wireless full-duplex (FD) technique focuses on improving the spectrum efficiency and raising the system throughput. In this paper, the vehicle-to-vehicle (V2V) links are deployed in an FD cellular network. However, the resource allocation and power control become challenging, due to the excess self-interference (SI) at the FD base station (BS) and the interference from the V2I uplink to downlink sharing the same resource block (RB). A Dual Graph Coloring-based Interference Management (DGCIM) scheme is proposed to solve the tricky problem. The DGCIM scheme includes a GrouPing Graph Coloring with Recursive Largest First (GPGC-RLF) algorithm and a GreedY Graph Coloring (GYGC) algorithm. The simulation results illustrate the guarantee of the stringent reliability and latency constraint for V2V links. The Jain’s index of the V2I link, nearly two times that of a half-duplex (HD) scheme, further verifies the validity of the DGCIM scheme.

Intelligent Reflecting Surface and Artificial-Noise-Assisted Secure Transmission of MEC System

Mobile-edge computing (MEC) and intelligent reflecting surface (IRS) have attracted much attention as promising technologies for the next-generation mobile networks and Internet of Things (IoT). In this article, we investigate how to improve the security of the MEC system with the assistance of IRS and artificial noise (AN) in the IoT. By adjusting the phase of the IRS, the users’ signals can be enhanced and the eavesdroppers’ signal can be weakened. In addition, the full-duplex base station (FD-BS) transmits AN to destroy the eavesdroppers’ signal and further enhance the users’ security. We minimize the users’ secure energy consumption by jointly optimizing the base station receive beamforming vectors, AN covariance matrix, IRS phase shifts, users’ offloading time, transmit power, and local computation tasks. The formulated problem is a nonconvex problem that is hard to solve directly, so we decompose it into tractable subproblems and develop an alternating optimization approach by combining the semidefinite relaxation (SDR) algorithm and Dinkelbach’s method. The results show that the proposed scheme can greatly reduce the secure energy consumption compared with other benchmark scheme.

On the Degrees of Freedom Region for Simultaneous Imaging &amp; Uplink Communication

In this paper, we take the first step towards quantifying the fundamental performance trade-offs between imaging and communication supported simultaneously using the same network resources. We analyze an uplink system configuration with a full-duplex base station (BS) illuminating an imaging scene while receiving data from a communication user. Our main contributions are two-fold. First, we propose a unified signal space analysis framework based on the degrees of freedom metric to characterize the trade-offs between the two operations in the high signal-to-noise ratio regime. Second, we propose a dual-function joint processing scheme, decode-and-image, that allows the BS to simultaneously form an image of the scene while decoding the uplink user&#x2019;s data. Our analysis and proposed scheme highlight the benefits of exploiting the uplink signals for imaging, at the cost of increased cooperation between the BS and uplink user. Moreover, our proposed scheme outperforms traditional schemes that enable dual-function operation via spatial or temporal isolation of imaging and communication signals.

Spatially-Correlated IRS-Aided Multiuser FD mMIMO Systems: Analysis and Optimization

We consider a two-way full-duplex (FD) system where a massive multi-input-multi-output FD base station (BS) communicates with multiple FD users via an intelligent reflecting surface (IRS). We derive a closed-form network spectral efficiency lower bound by considering spatial correlation at the BS and IRS. We demonstrate the importance of modelling spatial correlation by simplifying this lower bound for uncorrelated channels to show that the IRS capability to modify the wireless medium now is significantly impeded. This lower bound, which is a function of only the long-term channel statistics, is also used to maximize the non-concave global energy efficiency metric by optimally allocating the transmit powers, and by designing the IRS phases. We derive closed-form updates for optimizing the transmit powers using Lagrangian dual, Quadratic, and Dinkelbach’s transforms. We then optimize the IRS phases by using the projected gradient ascent algorithm. We numerically show that increasing the number of IRS elements can help a FD mMIMO BS outperform its half-duplex counterpart, which otherwise under-performs due to its limited ability to cancel various FD interferences.

Opportunistic Temporal Fair Mode Selection and User Scheduling in Full-Duplex Systems

In-band full-duplex (FD) communication has emerged as one of the promising techniques to improve data rates in next generation wireless systems. Typical FD scenarios considered in the literature assume FD base stations (BSs) and half-duplex (HD) users activated either in uplink (UL) or downlink (DL), where inter-user interference (IUI) is treated as noise at the DL user. This paper considers more general FD scenarios where an arbitrary fraction of the users are capable of FD and/or they can perform successive interference cancellation (SIC) to mitigate IUI. Consequently, one user can be activated in either UL or DL (HD-UL and HD-DL modes), or simultaneously in both directions requiring self-interference mitigation (SIM) at that user (FD-SIM mode). Furthermore, two users can be scheduled, one in UL and the other in DL (both operating in HD), where the DL user can treat IUI as noise (FD-IN mode) or perform SIC to mitigate IUI (FD-SIC mode). This paper studies opportunistic mode selection and user scheduling under long-term and short-term temporal fairness in single-carrier and multi-carrier (OFDM) FD systems, with the goal of maximizing system utility (e.g. sum-rate). First, the feasible region of temporal demands is characterized for both long-term and short-term fairness. Subsequently, optimal temporal fair schedulers as well as practical low-complexity online algorithms are devised. Simulation results demonstrate that using SIC to mitigate IUI as well as having FD capability at users can improve FD throughput gains significantly especially, when user distribution is concentrated around a few hotspots.

Sensing-Assisted Secure Uplink Communications With Full-Duplex Base Station

This letter proposes a sensing-assisted uplink communications framework between a single-antenna user and a full-duplex (FD) base station (BS) against an aerial eavesdropper (AE). To protect the information from being overheard, the BS transmits radar signals to localize and jam AE while receiving uplink signals. The radar signal transmission is divided into detection phase and tracking phase. In detection phase, the BS synthesizes a wide beam to localize the AE under the secrecy rate constraint; while in tracking phase, the BS maximizes the signal-to-interference-plus-noise ratio (SINR) of its received signals under the AE’s SINR constraint while guaranteeing a predefined radar echo signal signal-to-noise ratio (SNR) level. To deal with the self interference, we jointly optimize the radar waveform and receive beamforming vector. An alternating optimization algorithm and a successive convex approximation (SCA) based algorithm are proposed to solve the two formulated problems, respectively. Simulation results verify the effectiveness of the proposed algorithms. They also show that the secrecy rate can be significantly improved with the assistance of BS sensing.

Rate Maximization in a UAV Based Full-Duplex Multi-User Communication Network Using Multi-Objective Optimization

In this paper, we study an unmanned-aerial-vehicle (UAV) based full-duplex (FD) multi-user communication network, where a UAV is deployed as a multiple-input–multiple-output (MIMO) FD base station (BS) to serve multiple FD users on the ground. We propose a multi-objective optimization framework which considers two desirable objective functions, namely sum uplink (UL) rate maximization and sum downlink (DL) rate maximization while providing quality-of-service to all the users in the communication network. A novel resource allocation multi-objective-optimization-problem (MOOP) is designed which optimizes the downlink beamformer, the beamwidth angle, and the 3D position of the UAV, and also the UL power of the FD users. The formulated MOOP is a non-convex problem which is generally intractable. To handle the MOOP, a weighted Tchebycheff method is proposed, which converts the problem to the single-objective-optimization-problem (SOOP). Further, an alternative optimization approach is used, where SOOP is converted in to multiple sub-problems and optimization variables are operated alternatively. The numerical results show a trade-off region between sum UL and sum DL rate, and also validate that the considered FD system provides substantial improvement over traditional HD systems.

Practical Hybrid Beamforming for Millimeter Wave Massive MIMO Full Duplex With Limited Dynamic Range

Full Duplex (FD) radio has emerged as a promising solution to increase the data rates by up to a factor of two via simultaneous transmission and reception in the same frequency band. This paper studies a novel hybrid beamforming (HYBF) design to maximize the weighted sum-rate (WSR) in a single-cell millimeter wave (mmWave) massive multiple-input-multiple-output (mMIMO) FD system. Motivated by practical considerations, we assume that the multi-antenna users and hybrid FD base station (BS) suffer from the limited dynamic range (LDR) noise due to non-ideal hardware and an impairment aware HYBF approach is adopted by integrating the traditional LDR noise model in the mmWave band. In contrast to the conventional HYBF schemes, our design also considers the joint sum-power and the practical per-antenna power constraints. A novel interference, self-interference (SI) and LDR noise aware optimal power allocation scheme for the uplink (UL) users and FD BS is also presented to satisfy the joint constraints. The maximum achievable gain of a multi-user (MU) mmWave FD system over a fully digital half duplex (HD) system with different LDR noise levels and numbers of the radio-frequency (RF) chains is investigated. Simulation results show that our design outperforms the HD system with only a few RF chains at any LDR noise level. The advantage of having amplitude control at the analog stage is also examined, and additional gain for the mmWave FD system becomes evident when the number of RF chains at the hybrid FD BS is small.

Transmit Power Optimization of Simultaneous Transmission and Reflection RIS Assisted Full-Duplex Communications

Reconfigurable intelligent surface (RIS) has been proven to be a promising technology for improving the performance of future wireless systems. However, since conventional RIS can only reflect or transmit (i.e., refract) incident signals, it limits the applications of RISs. Fortunately, a novel simultaneous transmission and reflection reconfigurable intelligent surface (STAR-RIS) is proposed to improve the convenience of communication. By altering the electromagnetic properties of the STAR-RIS elements with a smart controller, it can split the incident signal into transmission and reflection signals, achieving 360° coverage. This work demonstrates the effectiveness of STAR-RIS aided full-duplex (FD) communication system, where a FD base station (BS) communicates with an uplink (UL) user and a downlink (DL) user simultaneously over the same time-frequency dimension assisted by a STAR-RIS. The objective is to minimize the total transmit power subject to the given minimal data rate requirement. We decouple the original problem into power optimization and STAR-RIS passive beamforming subproblems and adopt the alternating optimization (AO) framework to solve them iteratively. Specifically, in each iteration, we derive the closed-form expression for the optimal power design, then use the successive convex approximation (SCA) method and semidefinite program (SDP) to solve the passive beamforming optimization subproblem. Simulation results verify the convergence and effectiveness of the proposed algorithm and further reveal the performance gain compared with the half-duplex (HD) and conventional RIS.

Intelligent Non-Orthogonal Beamforming With Large Self-Interference Cancellation Capability for Full-Duplex Multiuser Massive MIMO Systems

This work introduces a novel full-duplex hybrid beamforming (FD-HBF) technique for the millimeter-wave (mmWave) multi-user massive multiple-input multiple-output (MU-mMIMO) systems, where a full-duplex (FD) base station (BS) simultaneously serves half-duplex (HD) downlink and uplink user equipments over the same frequency band. Our main goal is jointly enhancing the downlink/uplink sum-rate capacity via the successful cancellation of the strong self-interference (SI) power. Furthermore, FD-HBF remarkably reduces the hardware cost/complexity in the mMIMO systems by interconnecting the radio frequency (RF) and baseband (BB) stages via a low number of RF chains. First, the RF-stage is constructed via the slow time-varying angular information, where two schemes are proposed for both maximizing the intended signal power and canceling the SI power. Particularly, orthogonal RF beamformer (OBF) scheme only aims canceling the far-field component of SI, while non-orthogonal RF beamformer (NOBF) scheme applies perturbations to the orthogonal beams for also suppressing the near-field component of SI channel. Considering the high computational complexity during the search for optimal perturbations, we apply swarm intelligence to find the optimal perturbations. Second, the BB-stage is designed based on only the reduced-size effective intended channel matrices, where the BB precoder/combiner solutions are obtained via regularized zero-forcing (RZF) and minimum mean square error (MMSE). Hence, the proposed FD-HBF technique does not require the instantaneous SI channel knowledge. It is shown that FD-HBF with NOBF+MMSE achieves 78.1 dB SI cancellation (SIC) on its own. Additionally, FD-HBF with the practical antenna isolation can accomplish more than 130 dB SIC and reduce the SI power below the noise floor. The numerical results present that FD-HBF greatly improves the sum-rate capacity by approximately doubling it compared to its HD counterpart.

Joint Transmitter-Receiver Optimization and Self-Interference Suppression in Full-Duplex MIMO Systems

In this paper, we study the effects of joint transmit and receive antennas’ selection on full-duplex (FD) multiple-input-multiple-output (MIMO) networks’ performance. The antennas’ selection problem is, in general, a combinatorial problem whose complexity grows exponentially with the number of antennas. To fully understand the effects of antennas’ selection, we study the sum rate maximization problem in a single-cell network with an FD-MIMO base-station (BS). First, we consider a system with a normal-scale MIMO full-duplex BS, i.e., a normal-scale FD MIMO system. The sum rate maximization problem is studied for two different scenarios; in the first scenario, we consider jointly optimizing the transmit and receive antennas’ selection with the precoder and the receiver weights. A Generalized Bender's Decomposition based algorithm is proposed to solve the mixed-integer nonlinear sum rate maximization problem. In the second scenario, we consider self-interference cancellation via zero-forcing (ZF) transmission. A heuristic algorithm is proposed to solve the sum rate maximization problem by optimizing the selection of the transmit antennas, receive antennas, and the receive antennas at which self-interference is nulled. Second, in a very-large scale, i.e., massive MIMO system, we derive lower bounds for the uplink and downlink rates with ZF receiver and precoder, respectively. The sum rate is maximized by jointly optimizing the transmit to receive antennas ratio and the ratio of the receive antennas at which self-interference is nulled. Finally, via numerical analysis, we evaluate the performance of the formulated sum rate maximization problems.