Uplink Research Articles

Uplink Outage Performance of NOMA-Based Hybrid Satellite-Terrestrial Relay Networks Over Generalized Inhomogeneous Fading Channels

In this paper, we investigate the outage performance of an uplink (UL) non-orthogonal multiple access (NOMA)-based hybrid satellite-terrestrial relay network (HSTRN), in which two users communicate with the satellite through a decode-and-forward (DF) relay due to the lack of direct link. To provide a comprehensive yet hitherto unexplored outage analysis framework, we consider a more generalized channel model, i.e., the terrestrial and satellite links, respectively, undergo <inline-formula> <tex-math notation="LaTeX">$\alpha -\mu $ </tex-math></inline-formula> and <inline-formula> <tex-math notation="LaTeX">$\kappa -\mu $ </tex-math></inline-formula> shadowed fadings. Under fixed power allocation (FPA) for both multiple access phase and relaying phase, we firstly study three successive interference cancellation (SIC) decoding schemes, of which the first two are refined from existing schemes, while the third one, named as <i>extended SIC (ESIC)</i>, is proposed in this paper to satisfy the quality of service (QoS) decoding criterion, which is shown to offer better performances for both users as compared to the former two SIC schemes. We also propose a novel dynamic power allocation (DPA) scheme for the multiple access phase, termed as <i>enhanced DPA (EDPA)</i>, to overcome both users&#x2019; error floor (EF) issue yet provide better user fairness than the conventional DPA in the literature. We then analyze the exact and asymptotic outage performance for three SIC and the <i>EDPA</i> schemes under the generalized channel setting. It is shown that both the proposed <i>ESIC</i> and <i>EDPA</i> can circumvent the EF issue and moreover, each has its own advantage in terms of the diversity order (DO). Our results also reveal that there exists a trade-off between <i>ESIC</i> and <i>EDPA</i>, since the former requires a premise on users&#x2019; targets rates to overcome the EF and once this premise is satisfied, no DO degradation will occur, while the latter does not entail such a premise but may face potential DO degradation. Finally, we present numerical results to verify the theoretical analysis, manifest the impacts of key parameters on the system performance, and demonstrate the advantages of our proposed network over other benchmarks.

Optimization of Grant-Free NOMA With Multiple Configured-Grants for mURLLC

Massive Ultra-Reliable and Low-Latency Communications (mURLLC), which integrates URLLC with massive access, is emerging as a new and important service class in the next generation (6G) for time-sensitive traffics and has recently received tremendous research attention. However, realizing efficient, delay-bounded, and reliable communications for a massive number of user equipments (UEs) in mURLLC, is extremely challenging as it needs to simultaneously take into account the latency, reliability, and massive access requirements. To support these requirements, the third generation partnership project (3GPP) has introduced enhanced grant-free (GF) transmission in the uplink (UL), with multiple active configured-grants (CGs) for URLLC UEs. With multiple CGs (MCG) for UL, UE can choose any of these grants as soon as the data arrives. In addition, non-orthogonal multiple access (NOMA) has been proposed to synergize with GF transmission to mitigate the serious transmission delay and network congestion problems. In this paper, we develop a novel learning framework for MCG-GF-NOMA systems with bursty traffic. We first design the MCG-GF-NOMA model by characterizing each CG using the parameters: the number of contention-transmission units (CTUs), the starting slot of each CG within a subframe, and the number of repetitions of each CG. Based on the model, the latency and reliability performances are characterized. We then formulate the MCG-GF-NOMA resources configuration problem taking into account three constraints. Finally, we propose a Cooperative Multi-Agent based Double Deep Q-Network (CMA-DDQN) algorithm to balance the allocations of the channel resources among MCGs so as to maximize the number of successful transmissions under the latency constraint. Our results show that the MCG-GF-NOMA framework can simultaneously improve the low latency and high reliability performances in massive URLLC.

Full-duplex cooperative uplink NOMA with adaptive decoding order

In this paper, a full-duplex (FD) cooperative uplink (UL) non-orthogonal multiple access (NOMA) network is studied, where a far user communicates with a base station via a direct link and user relaying. It is assumed that there exist randomly located M users in the vicinity wishing to share the same spectrum, one of which is selected and paired with far user by maxmin selection. The analytical derivations are performed for the outage probabilities of both users when three successive interference cancellation (SIC) schemes are adopted: channel state information (CSI)-based, quality of service (QoS)-based and hybrid SIC. The main issue in UL-NOMA networks is the inevitable error floor in the selected user's performance curves at high signal-to-noise ratio region. The hybrid SIC eliminates the error floor by adaptively changing the SIC decoding order and provides robustness to self-interference due to FD, in terms of selected user's outage performance, unlike the CSI-based and QoS-based SIC. It is shown that the selected user's performance can be further improved by power allocation besides the improved performance of far user by cooperation. The superiority of the hybrid SIC protocol for UL-FD-NOMA over reference half-duplex (HD) NOMA and OMA is demonstrated. Moreover, the results show that the performance of both users improves with increasing M.

Resource Allocation of Hybrid VLC/RF Systems With Light Energy Harvesting

In this paper, we study the problem of maximizing the sum throughput of <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">${K}$ </tex-math></inline-formula> users in a hybrid heterogeneous visible light communication (VLC)/radio frequency (RF) wireless communication system. This is done by optimizing the transmission time intervals of a time division multiple access (TDMA) scheme allocated to the users in two different downlink (DL) scenarios. In both scenarios, using the harvested energy, each user transmits its signal in an optimal allocated time interval over the uplink (UL) channel. In the first scenario, a lightwave powered communication network (LPCN)-based VLC system is used to radiate only optical energy to be harvested by the users over DL channel. Specifically, UL sum-rate maximization problem is formulated by optimizing UL time allocations. In the second scenario, a time switching-based simultaneous lightwave information and power transfer (TS-based SLIPT) is considered where the light-emitting diode (LED) transmitter sends both information and power simultaneously over DL channel. Specifically, we propose a multi-objective optimization problem (MOOP) to study the trade-off between the UL and DL sum-rates. The non-convex MOOP framework is then transformed into an equivalent form, which yields a set of Pareto optimal resource allocation policies. The effectiveness of the proposed approaches is illustrated through numerical results.

Reference signal design to mitigate co-channel interference in 5G OFDM systems with multiple numerologies

The 5G cellular technology is expected to support diverse services by flexible use of the allocated spectrum. It is achieved by allowing multiple subcarrier spacing and dynamically changing downlink (DL) and uplink (UL) transmissions based on the instantaneous traffic and latency requirements. The problem of mitigating co-channel interference (CCI) with different subcarrier spacings becomes more challenging, and the dynamic DL–UL configuration makes it further difficult. In this paper, a reference signal design to measure the CCI is proposed along with detailed mathematical analysis. Furthermore, novel algorithms to estimate the CCI are proposed which along with advanced receivers are used to effectively mitigate the interference. Simulations are performed to evaluate the performance of reference signal design and the proposed estimation algorithms. The results confirm the efficacy of the proposed methods.

Machine learning-aided pilot and power allocation in multi-cellular massive MIMO networks

This paper addresses the problem of power allocation (PA) and pilot assignment (PS) in the uplink (UL) of multi-user (MU) massive multiple-input multiple-output (M-MIMO) under pilot contamination (PC) regime. We analyzed the aforementioned problem with different constraints configurations representing practical and adverse conditions such as minimum quality of service (QoS) requirements. A machine learning (ML) approach based on the reward Q-Learning is deployed for implementing the resource allocation (RA) policy. The RA solution obtained with Q-Learning is compared with classical methods available in literature. We have considered different PC scenarios, generated by pilot reuse patterns. Several figures of merit, including spectral and energy efficiencies (SE, EE), bit error rate (BER) and convergence are analyzed considering different system and channel configurations. Extensive numerical simulation results demonstrate the effectiveness and efficiency in terms of performance-complexity trade-off of the proposed sequentially combined PS-PA method in multi-cellular massive MIMO systems.

Full-duplex cell-free mMIMO networks with coarse ADCs/DACs over Ricean fading for beyond 5G

In this article, we explore a practical full-duplex (FD) cell-free massive multiple-input multiple-output (mMIMO) network equipped with coarse analog-to-digital converters/digital-to-analog converters (ADCs/DACs) at the access points (APs) over Ricean fading channels for beyond 5G communication. First, we suppose that the minimum mean square error scheme is applied to estimate channel state information. The accurate sum achievable rate expressions for both uplink (UL) and downlink (DL) are obtained in closed-form by performing the maximum ratio combining and conjugate beamforming at the APs, respectively. Then, the expressions of energy efficiency for UL and DL can be obtained in closed-form based on the established power dissipation model. Finally, the numerical results are conducted to demonstrate our analytical results about the spectral efficiency of considered system. It is also found that when the total number of coarse ADCs/DACs precision is fixed, employing the higher-precision ADCs at the receive end of APs can notably improve the FD sum rate of proposed networks. In addition, the simulation results also show the impacts of number of antennas at each AP and resolution of coarse ADCs/DACs on the energy efficiency (EE) performance. It is revealed that the moderate quantization bits can contribute to the optimal EE.

Full-duplex transmission of multi-Gb/s subcarrier multiplexing and 5G NR signals in 39 GHz band over fiber and space

We propose a stable full-duplex transmission of millimeter-wave signals over a hybrid single-mode fiber (SMF) and free-space optics (FSO) link for the fifth-generation (5G) radio access networks to accelerate the Industry 4.0 transformation. For the downlink (DL), we transmit 39 GHz subcarrier multiplexing (SCM) signals using variable quadrature amplitude modulation (QAM) allocations for multi-user services. As a proof of operation, we experimentally demonstrate the transmission of 3 Gb/s SCM signals (1 Gb/s per user) over a hybrid system consisting of a 10 km SMF and 1.2 m FSO link. For the uplink (UL), satisfactory performance for the transmission of 2.4 Gb/s 5G new radio (NR) signal at 37 GHz over the hybrid system is experimentally confirmed for the first time, to the best of our knowledge. The measured error vector magnitudes for both DL and UL signals using 4/16/64-QAM formats are well below the third generation partnership project (3GPP) requirements. We also further evaluate by simulation the full-duplex transmission over the system in terms of received optical and RF powers and bit error rate performance. A wireless radio distance of approximately 200 m, which is sufficient for 5G small-cell networks, is estimated for both DL and UL direction under the heavy rain condition, based on the available data from Spain. Furthermore, simulation for the DL direction is conducted to verify the superior performance of the system using variable QAM allocation over uniform QAM allocation. Using a variable modulation allocation, up to five users (2 Gb/s per user) can be transmitted over a hybrid 10 km SMF and 150 m FSO link.

On the Theoretical Analysis of Network-Wide Massive MIMO Performance and Pilot Contamination

In this paper, we theoretically analyse the uplink (UL) and downlink (DL) performance of massive multiple-input and multiple-output (mMIMO) networks, in term of coverage probability, cell spectral efficiency and network area spectral efficiency, using stochastic geometry. A sophisticated but yet practical system model is considered, taking into account a path loss model differentiating line-of-sight and non-line-of-sight transmissions, an idle mode capability at the base stations and a finite user density. Our analysis pays particular attention to the existence of a finite number of UL pilots for channel estimation and the effect of pilot contamination. We study for the first time the joint impact of the number of UL pilot sequences, the user density, and the base-station density on the pilot contamination issue in a mMIMO network, which in turn characterizes the DL and UL network performance. Moreover, using the proposed framework, we investigate two different scheduling problems—UE and pilot scheduling—, to find the optimal simultaneously scheduled UE density per time-frequency resource as well as the optimal UL pilot number to maximise the spectral efficiency.

Transceiver Design and Power Control for Full-Duplex Ultra-Reliable Low-Latency Communication Systems

Ultra-reliable low-latency communication (URLLC) is one of the most important components in the fifth generation (5G) cellular networks for realizing mission-critical applications. In this paper, we jointly optimize the transceiver design and decoding error probability (DEP) of a full-duplex (FD) URLLC system, where the base station (BS) operates in FD mode, while the uplink (UL) and downlink (DL) users work in half-duplex (HD) mode. Accordingly, an optimization problem is formulated to maximize the achievable total (UL plus DL) rate for an FD URLLC system under finite blocklength, subject to the end-to-end (E2E) reliability constraint from the UL user to each DL user and the total transmission power constraint at the UL user and at the BS. We analyze the problem structure and convexify the problem by approximating the channel dispersion in scenarios of high and mid-to-high signal-to-interference plus noise ratio (SINR) regimes, respectively. Next, efficient iterative algorithms are proposed to find the near-optimal power allocation for the UL user and transceiver weights for the BS. Furthermore, closed-form expressions of the transceiver weights are derived, and the convergence of the proposed algorithms is proved. Simulation examples demonstrate the impact of the code blocklength, number of DL users, transmitter/receiver distortion and DEP threshold on the system performance.

A SIC-Based BS Coordination Scheme for Full Duplex Cellular Networks

Full Duplex (FD) in cellular networks is expected to increase the cell spectral efficiency. However, while the downlink (DL) spectral efficiency (SE) increases with FD, the uplink (UL) SE decreases because of the Base Station to Base Station (BS) interference. In this paper, assuming a three-node model, we propose a method based on Successive Interference Cancellation (SIC) to reduce the BS-to-BS interference present in FD cellular networks. The approach consists in coordinating BSs to enable the decoding and the suppression of undesired signals that impair uplink transmissions. We analyze both distributed and Centralized Radio Access Networks (CRAN) architectures. Stochastic geometry is used to derive the coverage probability and mean data rate of the proposed scheme. In the distributed scenario, the FD UL average data rate is increased by 25% with our solution compared to a classical FD network, while our FD scheme still outperforms Half-Duplex (HD) on the DL. In the centralized scenario, our solution outperforms HD by 10% and classical FD by 78% on the UL, while preserving classical FD gains on the DL.

Uplink Performance of MmWave-Fronthaul Cell-Free Massive MIMO Systems

Cell-free (CF) massive multiple-input multiple-output (mMIMO) is a promising candidate to support the requirements of the fifth-generation (5 G) and beyond networks. However, the capacity of the fronthaul network dramatically influences its performance. While wired fronthaul links can be seen as the optimal choice, they may not be practically feasible. Exploiting the enormous bandwidth available in the millimeter-Wave (mmWave) band to support the fronthaul links paves the way to achieve the full potential of CF mMIMO systems. In this paper, we investigate the uplink (UL) performance of CF mMIMO systems supported by mmWave-fronthaul networks. Using tools from stochastic geometry, we derive analytical expressions for both the distribution of the provided fronthaul capacity and the average UL data rates. We show that although increasing the density of blockages degrades the average UL data rates, increasing the density of CPUs can limit such effect. Moreover, the obtained results reveal that the network deployment should be adjusted according to the available fronthaul bandwidth and the density of blockages. In particular, for a given fronthaul bandwidth, increasing the density of APs beyond a certain limit would not achieve further improvement in the UL data rates. Besides, increasing the number of antennas per AP may even cause a degradation in the system performance.

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.

Hybrid Direction of Arrival Precoding for Multiple Unmanned Aerial Vehicles Aided Non-Orthogonal Multiple Access in 6G Networks

Unmanned aerial vehicles (UAV) have attracted increasing attention in acting as a relay for effectively improving the coverage and data rate of wireless systems, and according to this vision, they will be integrated in the future sixth generation (6G) cellular network. Non-orthogonal multiple access (NOMA) and mmWave band are planned to support ubiquitous connectivity towards a massive number of users in the 6G and Internet of Things (IOT) contexts. Unfortunately, the wireless terrestrial link between the end-users and the base station (BS) can suffer severe blockage conditions. Instead, UAV relaying can establish a line-of-sight (LoS) connection with high probability due to its flying height. The present paper focuses on a multi-UAV network which supports an uplink (UL) NOMA cellular system. In particular, by operating in the mmWave band, hybrid beamforming architecture is adopted. The MUltiple SIgnal Classification (MUSIC) spectral estimation method is considered at the hybrid beamforming to detect the different direction of arrival (DoA) of each UAV. We newly design the sum-rate maximization problem of the UAV-aided NOMA 6G network specifically for the uplink mmWave transmission. Numerical results point out the better behavior obtained by the use of UAV relays and the MUSIC DoA estimation in the Hybrid mmWave beamforming in terms of achievable sum-rate in comparison to UL NOMA connections without the help of a UAV network.

Network sum-rate maximization via joint power allocation and antenna selection for clustered downlink/uplink NOMA networks

This paper considers the problem of joint power allocation and antenna selection (J-PA-AS) for downlink (DL) and uplink (UL) clustered non-orthogonal multiple-access (NOMA) networks. In particular, the goal is to perform antenna selection for each user cluster and allocate transmit power to its users so as to maximize the network sum-rate in the DL and UL directions, while satisfying quality-of-service (QoS) requirements. The formulated problem happens to be non-convex and NP-hard, and thus, there is no systematic or computationally-efficient approach to solve it directly. In turn, a low-complexity two-stage algorithm is proposed. Specifically, the first stage optimally solves the sum-rate maximizing power allocation for each (antenna, user cluster) pair. After that, antenna selection is optimally solved in polynomial-time complexity via the Kuhn–Munkres with backtracking (KMB) algorithm. Extensive simulation results are provided to validate the proposed algorithm, which is shown to efficiently yield the optimal network sum-rate in each link direction, in comparison to the optimal J-PA-AS scheme (solved via a global optimization package), and superior to other benchmark schemes. Light is also shed on the impact of spatial-diversity on the network sum-rate, where it is shown that the greater the number of base-station antennas is, the higher the network sum-rate, and the lower the outage events. Additionally, the significance of decoupling antenna selection in each link direction on the network sum-rate is highlighted. Lastly, the cases of imperfect channel state information (CSI) and imperfect successive interference cancellation (SIC) have been investigated, where it is demonstrated that spatial-diversity gains reduce the adverse effects of imperfect CSI and SIC on the network sum-rate.

Transmitter and receiver design for integrated full‐duplex multiple‐input‐multiple‐output communication and multiple‐input‐multiple‐output radar system

This study discusses the integrated system of full-duplex (FD) multiple-input-multiple-output (MIMO) communication and MIMO radar, which has been rarely considered in published studies. Such an integrated system is composed of a base station and several uplink (UL) and downlink (DL) users, and is supposed to simultaneously implement three functionalities, that is, target detection, UL and DL communications. The degrees of freedom of system design involve the precoding and combining schemes for UL and DL communications, as well as the receiving filter for radar echo. An optimization problem is developed to maximise a compound communication sum-rate metric subject to the SINR constraint imposed on target detection performance. The resulted non-convex and NP-hard problem is first divided into two sub-problems. Then, for one of the sub-problems that is still intractable, its solution is iteratively obtained based on the fractional programing technique and the consensus alternating direction method of multipliers algorithm. In the simulation part, the convergence performance and computational efficiency of the proposed algorithm are illustrated. In addition, the target detection performance, DL and UL communication performance of the integrated system are also evaluated.

Channel Estimation and Prediction in a Pilot-Less Massive MIMO TDD Using Non-Coherent DMPSK

A novel time division duplex massive MIMO technique is proposed based on performing a pilot-less channel estimation in the uplink (UL) utilizing reconstructed differentially encoded data. Spatial multiplexing and differentially encoded data is applied both in the UL and in the downlink (DL). In this system, a reference signal is the first one of the differentially encoded streams in the UL and DL, and the pilots for data estimation are avoided while maintaining spatial multiplexing capabilities. To improve the channel estimation we propose to use a linear Wiener filter and we also propose different symbols placing strategies in an OFDM grid. We also propose a detection improvement of the UL data utilizing the predicted channels. We perform an analysis of the MSE of the blind channel estimation using the differentially encoded data and analyze the symbol-error-rate for both the UL and the DL when channel aging is considered. The analysis is corroborated via numerical results and the proposed scheme is shown to outperform its pilot-based counterpart.

Energy Efficiency Trade-off with Spectral Efficiency in MIMO Systems

5G technology can greatly improve spectral efficiency (SE) and throughput of wireless communications. In this regard, multiple input multiple output (MIMO) technology has become the most influential technology using huge antennas and user equipment (UE). However, the use of MIMO in 5G wireless technology will increase circuit power consumption and reduce energy efficiency (EE). In this regard, this article proposes an optimal solution for weighing SE and throughput tradeoff with energy efficiency. The research work is based on the Wyner model of uplink (UL) and downlink (DL) transmission under the multi-cell model scenario. The SE-EE trade-off is carried out by optimizing the choice of antenna and UEs, while the approximation method based on the logarithmic function is used for optimization. In this paper, we analyzed the combination of UL and DL power consumption models and precoding schemes for all actual circuit power consumption models to optimize the trade-off between EE and throughput. The simulation results show that the SE-EE trade-off has been significantly improved by developing UL and DL transmission models with the approximation method based on logarithmic functions. It is also recognized that the throughput-EE trade-off can be improved by knowing the total actual power consumed by the entire network.

Intelligent Reflecting Surface Aided Full-Duplex Communication: Passive Beamforming and Deployment Design

This paper investigates the passive beamforming and deployment design for an intelligent reflecting surface (IRS) aided full-duplex (FD) wireless system, where an FD access point (AP) communicates with an uplink (UL) user and a downlink (DL) user simultaneously over the same time-frequency dimension with the help of IRS. Under this setup, we consider three deployment cases: 1) two distributed IRSs placed near the UL user and DL user, respectively; 2) one centralized IRS placed near the DL user; 3) one centralized IRS placed near the UL user. In each case, we aim to minimize the weighted sum transmit power consumption of the AP and UL user by jointly optimizing their transmit power and the passive reflection coefficients at the IRS (or IRSs), subject to the UL and DL users' rate constraints and the uni-modulus constraints on the IRS reflection coefficients. First, we analyze the minimum transmit power required in the IRS-aided FD system under each deployment scheme, and compare it with that of the corresponding half-duplex (HD) system. We show that the FD system outperforms its HD counterpart for all IRS deployment schemes, while the distributed deployment further outperforms the other two centralized deployment schemes. Next, we transform the challenging power minimization problem into an equivalent but more tractable form and propose an efficient algorithm to solve it based on the block coordinate descent (BCD) method. Finally, numerical results are presented to validate our analysis as well as the efficacy of the proposed passive beamforming design.

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.