Uplink Capacity Research Articles

Novel Listen-Before-Talk Access Scheme With Adaptive Backoff Procedure for Uplink Centric Broadband Communication

To cater for the data-hungry Internet of Things (IoT) applications, Uplink Centric Broadband Communication (UCBC) has been identified as a new service class in the vision of 5.5G, where the unlicensed spectrum has been regarded as a promising solution to boost the uplink capacity. The New Radio Unlicensed (NR-U) network adopts Category-4 (Cat4) Listen Before Talk (LBT) access scheme to exploit the unlicensed spectrum and fairly coexist with the incumbent Wireless Fidelity (WiFi) network. However, the existing Cat4 LBT access scheme adopts single fixed energy detection (ED) threshold and Backoff speed, which cannot adapt to the sophisticated interference and achieve the expected uplink system throughput. To tackle this issue, in this paper, we develop a novel Cat4 LBT access scheme with adaptive Backoff procedure for UCBC, which includes instantaneous interference level quantification, instantaneous interference level sharing, and Backoff speed determination. The results have shown that our proposed adaptive Cat4 LBT scheme achieves over 70% uplink system throughput performance gain where cell throughput of NR-U network rises by over 100%, and cell throughput of WiFi network increases by 25%.

Performance and Capacity Optimization for High Speed Railway Communications Using UAV-IRS Assisted Massive MIMO System

In this paper, we study the communication performance of applying unmanned aerial vehicles (UAVs) combined with intelligent reflective surfaces (IRS) in a high speed railway (HSR) scenario. This study investigates the design and performance of (multiple-input-multiple-output) MIMO systems with UAV and IRS assistance technology in high-mobility scenarios. Direct links between base stations (BS) and trains are often obstructed in suburban environments, especially in mountainous areas. We mount the IRS on the UAVs so that it can assist in the communication between the trains and the BS. With the help of the UAV-IRS, straight-line links can be established effectively, which greatly improves communication for train passengers. This paper considers the employment of large-scale antenna arrays at both the BS and train ends. Train passengers communicate with UAVs via antennas assembled on the roof of the train as gateways, which in turn communicate with the BS. We consider two types of antenna layouts on the train: all antennas are located in the center of the train named Co-located antennas (CA) layout and uniformly distributed along the train called distributed antennas (DA) layout. We can obtain the analytical up-link capacity by averaging over all locations in a cell for the above two layouts by considering the radio frequency consumption. Overall, the CA layout is found to be a better option for trains when attempting to maximize cell mean value of capacity, and DA layout achieves a more uniformly distribution of capacity over the entire cell. Ultimately, the best solution will depend on the specific requirements and constraints of the selected deployment scenario.

Concurrent Transmission and Multiuser Detection of LoRa Signals

This article investigates a new model to improve the scalability of low-power long-range (LoRa) networks by allowing a group of multiple end devices (EDs) to communicate with multiple multi-antenna gateways simultaneously (i.e., in the same time slot) on the same frequency band and using the same spreading factor. The maximum-likelihood (ML) decision rule is first derived for noncoherent detection of information bits transmitted by multiple devices in a group. To overcome the high complexity of the ML detection, we propose a suboptimal two-stage detection algorithm to balance the computational complexity and error performance. In the first stage, we identify transmitted chirps (without knowing which EDs transmit them). In the second stage, we determine the EDs that transmit the specific chirps identified from the first stage. To improve the detection performance in the second stage, we also optimize the transmit powers of EDs to minimize the similarity, measured by the Jaccard coefficient, between the received powers of any pair of EDs in the same group. As the power control optimization problem is nonconvex, we use concepts from successive convex approximation to transform it to an approximate convex optimization problem that can be solved iteratively and guaranteed to reach a suboptimal solution. Simulation results demonstrate and justify the tradeoff between transmit power penalties and network scalability of the proposed LoRa network model. In particular, by grouping two or three EDs in each group for concurrent transmission, the uplink capacity of the proposed network can be doubled or tripled over that of a conventional LoRa network, albeit at the expense of additional 3.0 or 4.7 dB transmit power.

Interference Management in Cellular-Connected Internet of Drones Networks With Drone-Pairing and Uplink Rate-Splitting Multiple Access

Interference management is a key challenge for cellular-connected Internet of Drones (IoD) networks that employ multiple cellular-connected hovering drones for data acquisition in surveillance and monitoring applications. This article proposes a novel resource optimization framework for managing interference in cellular-connected IoD networks. Specifically, the envisioned system divides the set of transmitting drones into distinct drone pairs, where the paired drones simultaneously transmit over the same radio resource blocks (RRBs). Each drone pair is assigned a set of orthogonal RRBs for data transmission, where these RRBs are shared with the terrestrial cellular network as well. An uplink rate-splitting multiple access scheme is employed to mitigate the interdrone interference at the drone pairs, and an RRB pricing method is exploited to control the interference between the aerial and cellular communication links. Our goal is to maximize the uplink capacity of the IoD network while reducing interference over the shared RRBs between the IoD and cellular networks. Toward this goal, a joint optimization of the drones’ transmit power allocation, drone pairing, and RRB scheduling among the drone pairs is presented. In order to obtain an efficient suboptimal solution, an iterative optimization is devised. Particularly, the presented joint optimization problem is decomposed into three subproblems for transmit power allocation, drone pairing and RRB scheduling, and RRB price update. By solving theses subproblems iteratively, a convergent rate-splitting-empowered resource allocation and clustering for interference management (REACT) algorithm is proposed. Extensive simulations are conducted to verify the effectiveness of the proposed REACT algorithm over several benchmark schemes.

Sphere detector with low complexity Euclidean distance computation based on affine transform modulation

The foreseen scale of connected autonomous and low power consumption devices in the near future is a challenging aspect for the next generation of mobile communication networks. As the number of available connection resources is limited, frequency-time multiplexing may not be sufficient to meet the expected demand for capacity, where scheduling solutions might incur in undesired latency levels and also increase the power expenditure to meet a more stringent synchronisation. In this scenario, spatial multiplexing based on multi-user multiple-input multiple-output can extend the uplink capacity at the cost of inter-antenna interference at the base station, requiring more complex detection schemes. The sphere detector can mitigate the inter-antenna interference, achieving close-to-optimum bit error rate performance with average polynomial complexity that still challenges the field programmable gate array implementation in terms of resources and area. To further reduce the sphere detector complexity, the authors introduce the concept of affine transform modulation, which allows us to describe the received signal in terms of the sequence of transmitted bits per symbol. The authors demonstrate that this approach allows to evaluate the Euclidean distance in the sphere detector algorithm in terms of the transmitted bits, replacing the complex inner product by a complex accumulator in its extensively accessed core function. The approach proposed in this paper leads to a considerable complexity reduction in terms of FLOPs for low-order modulations while attaining the conventional sphere detector performance.

Mega-Constellation Design for Integrated Satellite-Terrestrial Networks for Global Seamless Connectivity

In this letter, we study the integrated satellite-terrestrial network where users can access the core network by the backhaul links via both multi-layer satellites in the space and terrestrial access points on the ground. The mega-constellation design for such an integrated satellite-terrestrial network is investigated to realize the global seamless connectivity and provide high-rate backhaul transmission. First, we propose a theoretical framework for the average uplink capacity analysis. Second, based on the developed theoretical framework, we design a mega satellite constellation given the capacity of terrestrial backhaul links for realizing the global connectivity with the minimum satellite number. Simulation results show that as the terrestrial infrastructures are distributed more evenly in latitude, the designed mega-constellation first requires more satellites and then remains unchanged regardless of the terrestrial transmission capacity of high-latitude user terminals.

Collaborative and Efficient Body-to-Body Networks for IoT-Based Healthcare Systems

The recent advances in Internet of Things (IoT)-based healthcare systems pave the path for the development of body-to-body network (BBN), wherein a group of wireless body area network (WBAN) users collaborates and shares their individual resources. Since these WBAN users have individual decision-making capabilities and are self-centric in nature, they always aim to maximize their own performance while expecting benefits through resource sharing. In this article, we analyze the interaction among participating WBANs in BBN and develop joint data uploading and relaying strategy. In BBN, each WBAN not only utilizes its resources (uplink capacity and battery energy) to upload physiological data but also trades resources with other participating WBANs. Specifically, WBAN users with unused resources trade with other users deprived of Internet connection and low battery for mutual gain. Therefore, we model this interaction as an <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$N $ </tex-math></inline-formula> -person bargaining game and design an efficient incentive mechanism to facilitate user cooperation. The proposed mechanism ensures efficient resource sharing and fair division of mutual benefit among the participating WBAN users. Also, we propose a distributed algorithm for the practical implementation of the proposed mechanism in decentralized BBN. The simulation results demonstrate that the proposed mechanism always improves WBAN user’s individual performance together with the overall BBN performance. Furthermore, the overall performance increases with an increase in participating WBAN users’ resource heterogeneity.

A survey on downlink–uplink decoupled access: Advances, challenges, and open problems

The emergence of new uplink (UL) intensive applications, coupled with the ambitious vision of the Internet-of-Things (IoT), will soon unleash unprecedented increases in UL wireless data traffic. However, current network designs are mainly concerned with optimizing the downlink (DL) performance, hence cannot give full play to UL communications. Exacerbated by high path-loss and low UL to DL duration ratio in the 5G new radio time division duplex (TDD-NR) spectrum, the UL capacity is much smaller than that of the DL one. To overcome such a problem, a DL–UL decoupled access (DUDe) approach has been proposed, in which the users are allowed to connect to different base-stations (BSs) at different frequency bands in each link direction. Moreover, DUDe can be an add-on to many 5G (and beyond) technologies, such as millimeter-wave communication, multi-connectivity, device-to-device (D2D) communication, cellular-enabled unmanned aerial vehicle (UAV) communication, and mobile edge computing (MEC). However, despite the apparent consensus on its advantages, the realization of DUDe in 5G networks is in its infancy and still requires more efforts from both academia and industry. This survey provides a holistic overview on the DUDe approach, including operating bands DUDe (i.e. supplementary UL) and serving BS DUDe, reviews its fundamentals and explores potential use-cases. Other 5G UL coverage enhancement technologies, such as UL carrier aggregation, evolved universal terrestrial radio access-new radio (EUTRA-NR) dual connectivity (EN-DC), and UL Tx Switching are also compared with DUDe. Lastly, cutting edge research works in this area are summarized along with a discussion on the potential challenges and open research problems.

Multi-UAV Assisted IoT NOMA Uplink Communication System for Disaster Scenario

Unmanned aerial vehicle (UAV) communication has become a prominent technology that can effectively assist in IoT systems. The inherent features of UAV such as mobility, flexibility, and fast deployment make it preferable for emergency Internet of Things (IoT) applications. In this paper, we consider a multi-UAV assisted wireless network to support uplink communication for IoT devices distributed over a disaster area. The network involves two types of UAVs: sector UAV (SU) and anchor UAV (AU). The SU hovers at a fixed height over the sector around the temporary base station (TBS), collects the information from the respective IoT devices and relays them to the TBS via AU. The AU revolves continuously around the TBS and relays the information between the SUs and TBS periodically. We aim to improve the uplink capacity of the system. To achieve this, we employ non-orthogonal multiple access (NOMA), where we jointly optimize the positions of SUs and the power control of IoT devices. We propose a two-step approach to solve this. First, we optimize the position of SU in each sector by minimizing the sum distances of SU from the respective IoT devices. Then, by considering the optimal SU location, we optimize the transmit power of IoT devices using Lagrange dual method. Finally, the experimental results show that the proposed scheme improves the system capacity by 22% compared to the state-of-the-art schemes.

Scalable Cell-Free Massive MIMO Systems: Impact of Hardware Impairments

Standard cell-free (CF) massive multiple-input-multiple-output (mMIMO) systems is a promising technology to cover the demands for higher data rates in fifth-generation (5G) networks and beyond. These systems assume a large number of distributed access points (APs) using joint coherent transmission to communicate with the users. However, CF mMIMO systems present an increasing computational complexity as the number of users increases. Scalable cell-free CF (SCF) systems have been proposed to face this challenge. Given that the cost-efficient deployment of such large networks requires low-cost transceivers, which are prone to unavoidable hardware imperfections, realistic evaluations of SCF mMIMO systems should take them into account before implementation. Hence, in this work, we focus on the impact of hardware impairments (HWIs) on the SCF mMIMO systems through a general model accounting for both additive and multiplicative impairments. Notably, there is no other work in the literature studying the impact of phase noise (PN) in the local oscillators (LOs) of CF mMIMO systems or in general the impact of any HWIs in SCF mMIMO systems. In particular, we derive upper and lower bounds on the uplink capacity accounting for HWIs. Moreover, we obtain the optimal hardware-aware (HA) partial minimum mean-squared error (PMMSE) combiner. Especially, the lower bound is derived in closed-form using the theory of deterministic equivalents (DEs). Among the interesting findings, we observe that separate LOs (SLOs) outperform a common LO (CLO), and the additive transmit distortion degrades more the performance than the additive receive distortion.

Power Allocation in Massive MIMO‐HWSN Based on the Water‐Filling Algorithm

Pilot power allocation for Internet of Things (IoT) devices in massive multi‐input multioutput heterogeneous wireless sensor networks (MIMO‐HWSN) is studied in this paper. The interference caused by fractional pilot reusing in adjacent cells had a negative effect on the MIMO‐HWSN system performance. Reasonable power allocation for users can effectively weaken the interference. Motivated by the water‐filling algorithm, we proposed a suboptimal pilot transmission power method to improve the system capacity. Simulation results show that the proposed method can significantly improve the uplink capacity of the system and explain the influence of different pilot transmission power on the performance of the system, but the complexity of the system almost does not increase.

Cooperative Transmission of Energy-Constrained IoT Devices in Wireless-Powered Communication Networks

In Internet of Things (IoT) systems, a number of sensor devices monitor the physical system states and exchange information with each other. The main limitation is that the IoT devices are generally energy constrained since those are powered with batteries. To address this energy problem, we consider a cooperative wireless-powered communication network (WPCN), which consists of three phases: 1) downlink (DL) energy transfer from a multi-antenna access point (AP); 2) data sharing among IoT devices; and 3) uplink (UL) information transfer from single-antenna IoT devices. Based on the shared data and the harvested energy, the single-antenna IoT devices in the neighborhood cooperate to form a virtual antenna array in order to transmit their information simultaneously to the multi-antenna AP using a multiple-input multiple-output (MIMO) technique in the UL information transfer phase. In this study, the transmit covariance matrices (i.e., beamforming vectors and the corresponding transmit power allocation) used for both DL energy transfer and UL information transfer are jointly designed to maximize the UL capacity based on the Lagrangian method. Furthermore, the time allocation for each phase is optimized based on a stochastic gradient method. In the numerical results, it is shown that our proposed beamforming scheme and the stochastic time allocation can achieve near-optimal performance.

Joint Antenna Detection and Bayesian Channel Estimation for Non-Coherent User Terminals

In this paper, we propose a method of improving the channel estimates for non-coherent multi-antenna terminals, which are terminals that cannot control the relative phase between its antenna ports, with channels that can be considered constant over multiple time slots. The terminals have multiple antennas and are free to choose whichever antenna they want to use in each time slot. An unknown phase shift is introduced in each time slot as we cannot guarantee that the terminals are phase coherent across time slots. We compare three different clustering techniques that we use to detect the active antenna. We also compare a set of different statistical and heuristic estimators for the channels and the phase shifts. We evaluate the methods by using correlated Rayleigh fading and three different bounds on the uplink capacity. The accuracy of the capacity bounds are verified with bit-error-rate simulations. With our proposed methods we can have an SNR improvement of approximately 2 dB at 1 bit/s/Hz.

Analysis of 2-user ZF coordinated with user-wise MRTC diversity

Multi-user MIMO and spatial diversity are attractive techniques to improve the link capacity. In this paper, multi-user zero-forcing (ZF) coordinated with user-wise maximal-ratio transmitting and combining (MRTC) diversity is studied. A closed-form expression for the received signal-to-noise ratios (SNRs) achievable with 2-user ZF coordinated with user-wise MRTC diversity is derived for the given MIMO channel condition. It is shown from the derived SNR expression that the uplink capacity is higher than the downlink capacity and that the uplink capacity is not necessarily the same among users while the downlink SNR is always identical for users. This is confirmed by numerical evaluation assuming a Rayleigh fading environment.

Multi-User V-Band Uplink Using a Massive MIMO Antenna and a Fiber-Wireless IFoF Fronthaul for 5G mmWave Small-Cells

We experimentally demonstrate a multi-user Fiber Wireless IFoF/mmWave uplink comprising a 32-element 60 GHz Phased Array Antenna (PAA) and 10 km of fiber for 5G fronthaul networks, supporting beamsteering within a 120° sector and 0.6 Gb/s uplink capacity within a 5 dB bandwidth of 2 GHz. The flexibility of the link is highlighted in two 3-user scenarios with 0.6 Gb/s uplink traffic: A Frequency Division Multiplexing (FDM) scheme with the PAA receiving isotropically at different frequencies and a Spatial Division Multiplexing (SDM) scheme where the same V-band frequency is re-used by all three users but are selectively received by the PAA using beamsteering. Error-free transmission with 100 Mbaud QPSK per user is demonstrated for both cases, forming the first comparison of FDM and SDM towards multi-user 5G mmWave/IFoF networks.

Enabling Capacity Estimation With Ergodic Interference Power in Cellular-Based Multiple UAV Systems

The integration of unmanned aerial vehicles (UAVs) into cellular networks as aerial user equipment (aUE) has attracted increasing interest from both academia and industry in recent years. To ensure stable uplink (UL) service performance, the potential UL capacity must be determined for a variety of communication techniques to guide the system design or to obtain an optimized solution. Unlike traditional interferences from ground UEs, which contribute to only local and nearby cells, UAV systems involve strong LoS paths to even far side base stations (BSs) due to higher altitude. As a result, intercell interference becomes the dominating factor in the estimation of the potential capacity. In this article, we propose a theoretical model on the ergodic sum power of the interference arising from all UAVs maintaining LoS paths with the target BS. The solution to this model is difficult to obtain, and is essentially rooted in the dynamic trajectories of interfering UAVs within a vast geological range. To address this problem, we divide the model into noncorrelated parts, where each part contains the interfering UAVs that are independently and identically distributed (i.i.d.). Then we utilize the ergodic method to solve the interference power of each part. Based on this, the original nonanalytical expression for the ergodic sum interference power is transformed into a solvable integration problem, and the closed-form solution is successfully derived. Simulation based experiments are conducted on both rural macro (RMa) cell and urban macro (UMa) cell scenarios. The results validate the feasibility and accuracy of the proposed model, and confirm the severe influence of the intercell interference on the UL capacity.

Uplink Coverage and Capacity Analysis of mMTC in Ultra-Dense Networks

In this paper, we investigate the uplink coverage and ergodic capacity of massive Machine-Type Communication (mMTC) considering an Ultra-Dense Network (UDN) environment. In MTC, devices equipped with sensing, computation, and communication capabilities connect to the Internet providing what is known as Internet-of-Things (IoT). A dense network would provide an all-in-one solution where scalable connectivity, high capacity, and uniform deep coverage are byproducts. To account for short link distances, the path loss is modeled as stretched exponential path loss (SEPL). Moreover, the fading is modeled as a general $(\alpha -\mu)$ channel, where tractable and insightful results are derived for the Rayleigh fading special case. We consider the direct MTC access mode where mMTC nodes connect directly to the small cell. The analytical results disclose the impact of the system parameters and propagation environment parameters on the network performance. In particular, our results reveal that significant coverage enhancements and high uplink capacity are achievable at moderate cell densities, low transmission power, and moderate bandwidth. Moreover, the uplink network performance is independent of the maximum transmission power in the considered dense network scenario, allowing for longer battery lifetime of future IoT devices. The accuracy of the derived analytical results is assessed via extensive simulations.

Delivering Gigabit Capacities to Passenger Trains: Tales from an Operator on the Road to 5G

Delivering reliable and high-capacity Internet connectivity to high-speed train users is a challenge. Modern railway cars act as Faraday cages and a typical train consist comprises several hundreds of users moving at high velocity. Furthermore, with the global availability of fourth generation (4G) Long Term Evolution (LTE), user expectations have dramatically increased: it is expected to be online anytime and anywhere. Demand for mobile high-capacity is being driven by video and music streaming services, for lower latency and higher availability by gaming, and for more reliability and even uplink capacity by mission critical applications. Finally, the life-cycle of the railway industry is much longer than for telecommunications, which makes supporting 5G challenging. In this paper, we survey the challenges associated with delivering high-capacity connectivity to train users, describe potential options, and highlight how a leading western European operator is tackling these challenges and preparing for 5G and beyond.

Field Measurement for Antenna Configuration Comparison in Challenging NLOS Locations

This paper has two main objectives. First, it describes the practical challenges of field trials and proposes a developed test method. Second, the test method is used to compare the uplink (UL) performance with different antenna technologies when user equipment (UE) does not have a line of sight (LOS) to the evolved node B. Both passive and active antenna configurations were used in the performance evaluation. Modern cellular networks have high demands for capacity, reliability, and availability. The verification of a network’s configuration and technological features is essential to guarantee network performance, and the performance of a network must be verified by the laboratory testing or field trials; such trials produce the experimental knowledge of technology features and configurations. Technological and environmental factors must also be considered before performing mobile network field testing. This paper showed that moving UE produces more reliable and repeatable results than measurements with stationary UE. Our antenna configuration comparison study revealed that in the UL direction, active antenna system beam control could significantly increase the UL capacity in non-LOS conditions.

SU-MIMO based uplink non-orthogonal multiple access for 5G

In this paper, we present the application of single user multiple input multiple output (SU-MIMO) to uplink (UL) non-orthogonal multiple access (NOMA) to enhance UL capacity. However, SU-MIMO NOMA produces inter-stream interference in addition to intra-pair interference, leading to performance degradation. Therefore, a novel UL SU-MIMO NOMA signal detection, combining minimum mean square error (MMSE) with dual-level iterative successive interference cancelation is proposed to mitigate the interference. Additionally, generalized dynamic power allocation is proposed at UL transmitters to ensure the capacity for NOMA over orthogonal multiple access (OMA) and the capability to overcome error floor phenomenon caused by fixed power allocation. A practical SIC scheme is also considered to create a more realistic scenario than the perfect SIC. The proposed system is evaluated in terms of capacity, throughput, error performance, and computational complexity. The results show that the proposed SU-MIMO based NOMA outperforms in capacity, throughput, and error performance at the same MMSE complexity order.