Uplink Of Networks Research Articles

Rate Outage and Meta-Distribution for Uplink Networks in Finite Block-Length Regime

Rate Outage and Meta-Distribution for Uplink Networks in Finite Block-Length Regime

On the Adaptive Buffer-Aided TDMA Uplink System with AoI-Aware Status-Update Services and Timely Throughput Traffics.

In this paper, we study a buffer-aided TDMA uplink network, where multiple status-update devices and throughput-demand devices are supposed to upload their data to one information access point (AP), and all devices are assumed to be provisioned with a data buffer to temporarily store the randomly generated data from either the installed sensor or upper-layer applications. To fulfill the communication requirements using two types of devices, the average Age of Information (AoI) is utilized to characterize the data freshness of the status-update devices, while the average sum rate is employed to capture the average transmission performance of the throughput-demand devices. On this basis, a joint-optimization problem was formulated to minimize the average AoI for status-update devices and to maximize the average sum rate for the throughput-demand devices. Lyapunov optimization framework was used to solve the problem of obtaining an AoI-aware adaptive TDMA uplink scheme. Numerical results are presented to show that an AoI-aware adaptive TDMA uplink scheme can effectively fulfill the heterogeneous service requirements using status-update devices and throughput-demand devices.

Secrecy Energy Efficiency for Distributed-IRSs Assisted Uplink Networks

In this correspondence, we aim at achieving the energy-efficient secrecy transmission for an uplink network assisted by distributed intelligent reflecting surfaces (D-IRSs). The secrecy energy efficiency (SEE) maximization problem is investigated through jointly optimizing the discrete reflecting phase shifts, the transmit power, and the IRS switching status. To handle this non-convex problem, we decompose it into three subproblems, and then the majorization-minimization based algorithm, the Dinkelbach method and the Lagrangian dual method are adopted to obtain the solutions of reflecting phase shifts, transmit power and IRS switching status, respectively. The subproblems are alternatively optimized based on the iterative algorithm. Simulation results show that the proposed scheme can significantly improve the SEE compared to the centralized IRS, especially when the eavesdropping channel is stronger.

Optimal Phase Shift Design for Fair Allocation in RIS-Aided Uplink Network Using Statistical CSI

Optimal Phase Shift Design for Fair Allocation in RIS-Aided Uplink Network Using Statistical CSI

Optimizing Age of Information in Wireless Uplink Networks With Partial Observations

This paper considers a wireless uplink network consisting of multiple end devices and an access point (AP). Each device monitors a physical process with randomly generated status updates and sends these update packets to the AP in the uplink. The AP aims to schedule the transmissions of these devices to optimize the network-wide information freshness, quantified by the age of information (AoI) metric. Due to the stochastic arrival of the status updates at end devices, the AP only has partial observations of system times of the latest status update packets at end devices when making scheduling decisions. Such a decision-making problem can be naturally formulated as a partially observable Markov decision process (POMDP). We reformulate the POMDP into an equivalent belief Markov decision process (belief-MDP), by defining fully observable belief states of the POMDP as the states of the belief-MDP. The belief-MDP in its original form is difficult to solve as the dimension of its states can go to infinity and its belief space is uncountable. Fortunately, by carefully leveraging the properties of the status update arrival processes (i.e., Bernoulli processes), we manage to simplify the belief-MDP substantially, where every feasible state is characterized by a two-dimensional vector. Based on the simplified belief-MDP, we devise a low-complexity scheduling policy, termed Partially Observing Max-Weight (POMW) policy, for the formulated AoI-oriented scheduling problem. We derive upper bounds for the time-average AoI performance of the proposed POMW policy. We analyze the performance guarantee for the POMW policy by comparing its performance with a universal lower bound available in the literature. Numerical results validate our analyses and demonstrate that the performance gap between the POMW policy and its fully observable counterpart is proportional to the inverse of the lowest arrival rate of all end devices.

Adaptive Random Access and Data Transmission Scheme With Mixed Traffic in NGSO Satellite Networks

In non-geostationary orbit satellite networks, the resource is limited and the traffic under each satellite is in variation due to the motion of satellites and the non-uniform traffic on the ground. Generally, the uplink communication is guaranteed by successful random access (RA) and sufficient data transmission (DT) resources for various traffic types. Different traffic types usually have different requirements for resources, and joint resource management for mixed traffic tries to meet the needs of various traffic types at the same time and may improve uplink resource efficiency. However, existing strategies have not given integrative consideration to jointly allocate resources for RA and DT under dynamic mixed traffic demands, which leads to inefficient network resource utilization. Considering such a problem, we propose an adaptive random access and data transmission scheme for NGSO satellite networks in the mixed traffic scenario, considering two types of users, i.e., real-time users and best-effort users. Specifically, the utility functions of different types of users are introduced, and a utility-based access control and resource allocation algorithm is developed by solving the network utility maximization problem. Our scheme aims to achieve optimal uplink network utilization by adaptively controlling random access and allocating resources according to the dynamic demands of mixed traffic. Simulation results show that the proposed scheme outperforms other methods in terms of network utility, and exhibits near-optimal performance.

Secure wireless communications for STAR‐RIS‐assisted millimetre‐wave NOMA uplink networks

AbstractThis paper explores the potential application of simultaneously transmitting and reflecting reconfigurable intelligent surface (STAR‐RIS) in improving the physical layer security (PLS) of millimetre wave (mmWave) non‐orthogonal multiple access (NOMA) uplink communications. In particular, the legitimate users on both sides of STAR‐RIS send confidential information simultaneously to the base station (BS) while keeping it secret from the eavesdroppers near the BS by exploiting the STAR‐RIS to proactively regulate the electromagnetic propagation environment. By jointly designing the transmit power, the active beamforming at the BS, and the reflecting/transmitting coefficients at the STAR‐RIS, the authors' goal is to maximize the minimum secrecy capacity subject to the successive interference cancellation decoding order constraints. Due to the non‐convexity of the formulated problem, an efficient algorithm is proposed by capitalizing on alternating optimization, a penalty‐based approach, successive convex approximation, and semi‐definite relaxation. Firstly, a two‐layer iterative algorithm based on the penalty for the joint beamforming optimization sub‐problem is proposed. Then, the non‐convex problem is transformed into a convex positive semi‐definite programming problem for the transmit power sub‐problem. Numerical simulation results reveal that the STAR‐RIS‐aided system has more tremendous advantages and effectiveness in improving the PLS of mmWave NOMA uplink communication compared with the benchmark schemes.

A Super-Resolution Flexible Video Coding Solution for Improving Live Streaming Quality

In the context of the latest growing popularity of live video streaming, ensuring high video quality has become one of the most significant challenges faced by all live streaming platforms. Insufficient uplink bandwidth is an important factor that influences these live video transmissions, affecting their bitrate and latency and consequently the associated video streaming quality. This paper proposes a novel flexible super-resolution-based video coding and uploading framework (FlexSRVC) that improves the quality of live video streaming in limited uplink network bandwidth conditions. FlexSRVC includes a flexible video coding scheme, which compresses high-resolution key and non-key video frames to a lower bitrate in order to reduce the upload delay. A new flexible bitrate adaptation algorithm is also proposed to select dynamically the number of frames to be compressed and the compression ratio by jointly considering uplink network conditions and available cloud computing resources. Trace-driven emulations demonstrate that FlexSRVC provides the same quality while reducing up to 25% of the required bandwidth compared to the original encoding method (H.264). FlexSRVC improves users' QoE by at least 50% compared to a super resolution-based method which employs reconstruction of all video frames in uplink bandwidth constrained conditions.

On the Ergodic Rate of Cognitive Radio Inspired Uplink Multiple Access

With the exponential increase of the number of devices in the communication ecosystem toward the upcoming sixth generation (6G) of wireless networks, more enabling technologies and potential wireless architectures are necessary to fulfill the networking requirements of high throughput, massive connectivity, ultra reliability, and heterogeneous quality of service (QoS). In this work, we consider an uplink network consisting of a primary user (PU) and a secondary user (SU) and, by integrating the concept of cognitive radio and multiple access, two protocols based on rate-splitting multiple access and non-orthogonal multiple access with successive interference cancellation are investigated in terms of ergodic rate. The considered protocols aim to serve the SU in a resource block which is originally allocated solely for the PU without negatively affecting the QoS of the PU. We extract the ergodic rate of the SU considering a specific QoS for the PU for the two protocols and perform a qualitative and quantitative comparison between the two protocols. In the numerical results, we validate the theoretical analysis and illustrate the superiority of the considered protocols over two benchmark schemes.

Performance of CSI-Based Power Control and NOMA/OMA Switching for Uplink Underlay Networks With Imperfect SIC

In a multiuser underlay uplink network, we show that despite the fact that the transmit powers are constrained by the interference temperature limit (ITL) imposed by the primary network, allowing upto two users to concurrently transmit using non-orthogonal multiple access (NOMA) principles ensures better performance than when only a single user is picked in an orthogonal multiple access (OMA) scheme. To deal with the large variation in the link SNRs in underlay networks, an optimal channel state information (CSI) based ITL apportioning scheme is suggested for the first time in literature that carefully controls the transmit powers of the selected users to maximize throughput. CSI-based throughput-optimal strategies are evolved for user selection and NOMA/OMA switching. We analyze the throughput performance of the uplink with NOMA/OMA switching, optimal user selection, and CSI based ITL apportioning, taking successive interference cancellation (SIC) errors into account. Useful bounds on performance are also derived. It is shown that when the ITL is broadcast in every coherence interval, and the ITL can also be channel dependent, large thoughput gains accrue. Computer simulations confirm accuracy of the derived expressions.

Self-Adaptive Game Theoretic Approaches for Resource Allocation in SC-FDMA Based Heterogeneous Networks

We investigate the resource blocks (RBs) allocation problem in the Single-Carrier Frequency Division Multiple Access (SC-FDMA) based heterogeneous uplink networks from a game-theoretical viewpoint. First, a general network model that considers the co-tier, cross-tier, and inter-cell interference caused by the co-channel deployment is presented. Then, we design an effective throughput-optimizing utility function and prove it an exact potential game. The <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$\gamma$</tex-math></inline-formula> -logit is a learning algorithm which commonly used to achieve the optimal solution in potential game and is very sensitive to the changes of the network structures, making it hard in practice. To obtain the optimal solution under the different network structures stably, we propose a Self-adaptive logit algorithm, which can achieve the optimal solution automatically and is a variant of the well-established <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$\gamma$</tex-math></inline-formula> -logit learning algorithm. Additionally, to speed up the convergence, we propose the corresponding suboptimal algorithm based on the better response principle. Simulation results show that the proposed Self-adaptive logit algorithm is throughput optimal and network structure adaptive, outperforming the existing Binary-logit, Max-logit, and Round Robin algorithm. Moreover, the proposed suboptimal algorithm is near-optimal throughput achieved and converges efficiently. In addition, we also study the impact of the initial point selection on our proposed two alogithms.

Coordinated beamforming, interference-aware power control, and scheduling framework for 6G wireless networks

In this study, we propose a novel sum-rate enhancement framework for future 6G multi-cell multiple-input multiple-output (MIMO) uplink networks, which exploits the coordinated beamforming, power control, and user scheduling (CBPS) technique. The proposed CBPS technique not only significantly mitigates the inter-cell interference in transmit beamforming for users but also eliminates the intra-cell interference among the users in the same cell the receive beamforming at base stations (BSs). Additionally, we propose a user scheduling algorithm that selects the users whose effective channel vectors are mutually orthogonal to each other to increase the spectral efficiency and an interference-aware power control technique for users to further reduce inter-cell interference. It is worth noting that the proposed CBPS framework does not require information exchange among the BSs and operates in a non-iterative and distributed manner based on local channel state information (CSI) at both the BSs and users. Thus, it can be implemented for practical wireless systems with low complexity. Extensive simulation results show that the proposed CBPS framework significantly outperforms conventional techniques in multi-cell environments.

The Importance of Repetitions in Ultra-Dense NB-IoT Networks

This letter investigates the influence of the number of repetitions adopted in the NB-IoT standard to increase cellular coverage. We characterize the SINR in both uplink and downlink channels of ultra-dense networks, which is then used to derive the coverage probability and the NB-IoT’s capacity. The performance results show the effectiveness of the number of repetitions to reduce the block error rate for different densities of transmitters.

Secrecy sum rate maximization for a MIMO-NOMA uplink transmission in 6G networks

Non-orthogonal multiple access (NOMA), as a well-qualified candidate for sixth-generation (6G) mobile networks, has been attracting remarkable research interests due to high spectral efficiency and massive connectivity. The aim of this study is to maximize the secrecy sum rate (SSR) for a multiple-input multiple-output (MIMO)-NOMA uplink network under the maximum total transmit power and quality of service (QoS) constraints. Thanks to the generalized singular value decomposition method, the SSR of NOMA is compared with conventional orthogonal multiple access and other baseline algorithms in different MIMO scenarios. Due to the subtractive and non-convex nature of the SSR problem, the first-order Taylor approximation is exploited to transform the original problem into a suboptimal concave problem. Simulation results are provided and compared with some other benchmarks to evaluate the efficacy of the proposed method.

Next Generation Multiple Access: Performance Gains From Uplink MIMO-NOMA

The use of multiple-input multiple-output (MIMO) non-orthogonal multiple access (NOMA) based communication protocols is proposed and investigated for the uplink of wireless networks with buffered data-sources, which is the basis of the introduced medium access control (MAC)-layer protocol. To this end, the long-term average throughput is maximized by optimizing the set of users that transmit information at each time slot and their transmit power, the number of packets that are admitted in each user’s queue, and the transmission rates, assuming that the instantaneous channel state information is not available at the transmitters. Also, considering a receiver with multiple antennas, two detection techniques are used to mitigate the interference when two users are chosen to simultaneously transmit information in the same resource block, namely successive interference cancellation (SIC) and joint decoding (JD). More specifically, the outage probability for both considered techniques is derived in closed-from, which is a prerequisite for the derivation and the optimization of the throughput. The formulated multi-dimensional long-term stochastic optimization problem is solved by using the Lyapunov framework. Finally, simulation results verify the gains by using MIMO-NOMA as the basis of the next generation multiple access and illustrate the superiority of JD compared to SIC with respect to the number of the receiver’s antennas.

Rate maximization in full‐duplex systems: Gains and complexity of employing adaptive power allocation in downlink and/or uplink

AbstractThe next generations of mobile communications should deal with a set of new use cases, leading to a higher demand for spectral efficiency. Full‐duplex (FD) arises as a promising technology since it has the potential to double the system capacity without additional spectrum. However, FD networks are hindered by self‐interference (SI) and co‐channel interference caused by the reuse of frequency resources. Therefore, radio resource allocation (RRA) in FD networks by means of user pairing, frequency assignment, and power allocation are of utmost importance in order to improve spectral/energy efficiency and ensure quality of service (QoS). Although previous works investigated RRA to improve spectral efficiency, the fundamental question of where adaptive power allocation should be employed in the uplink and/or downlink of FD networks in a cost‐effective way remains unanswered. This article addresses this question in the context of total data rate maximization with QoS constraints where we propose four optimization problems using different power allocation strategies. The branch and bound method is employed to optimally solve the four formulated problems, which were used as upper bound solutions for benchmarking purposes. Moreover, we propose a low computational complexity solution able to adaptively switch the power allocation strategy depending on the scenario. Detailed system‐level simulations indicate that the best node to employ adaptive power allocation (mobile terminal or base station) depends on the cell radius and SI level. Also, our results show that, compared to existing solutions, the proposed low‐complexity is a great and intelligent strategy in terms of system performance and computational complexity considering both perfect and imperfect channel state information.

Energy Efficiency Maximization for IRS-Assisted Uplink Systems: Joint Resource Allocation and Beamforming Design

This letter investigates the design of resource allocation to maximize the energy efficiency (EE) in a multiuser multiple-input multiple-output (MIMO) intelligent reflecting surface (IRS)-assisted uplink network. The design is formulated as a mixed-integer non-convex optimization problem which jointly optimizes the antenna selection (AS) and power allocation at user sides and the beamforming matrices adopted at the BS and IRS. To facilitate the design of a suboptimal solution, we first decompose the original problem into two sub-problems via the alternative optimization (AO) method. In particular, for the first sub-problem, we propose an iterative algorithm based on the majorization minimization (MM) approach to make the numerator of the fractional problem into a concave form and then we employed the Dinkelbach algorithm. For the second sub-problem, we adopt the inner approximation (IA) method to optimize the beamforming matrices at the BS and IRS. Simulation results demonstrate the superiority of the proposed method over benchmark schemes for the case of a single antenna case and also provide considerable performance gains due to the use of an antenna selection strategy.

Computationally efficient scheduling methods for MIMO uplink networks

Computationally efficient scheduling methods for MIMO uplink networks

Majority Voting-Based MAC Protocol for Exploiting Link-Layer Diversity in Wireless Networks.

In wireless local area networks (WLANs), the effect of interference signals between neighboring nodes increases as the number of wireless nodes using limited radio frequency resources in a limited space increases, which can significantly degrade the reliability of data transmission. In high-density WLANs, there can be several neighboring access points (APs) that can receive uplink transmission from a station. In conventional medium access control (MAC) protocols, uplink data frames containing errors or transmitted from a non-associated station are discarded at APs. Alternatively, we propose a MAC protocol using redundant wireless links between neighboring APs and the non-associated stations. In the proposed MAC protocol, we consider a centralized WLAN with a control node that performs error corrections of erroneous uplink data frames via a majority voting algorithm-based link-layer diversity scheme using uplink data received from multiple APs to increase the reliability of data transmission. In addition, we propose an adaptive carrier sensing ranging mechanism to improve the uplink network throughput in the proposed centralized WLAN system. Further, we conduct simulation studies and software-defined radio-based experiments to evaluate the performance of the proposed MAC protocol in various WLAN scenarios.

Joint rate maximization of downlink and uplink in NOMA SWIPT systems

The combination of Non-orthogonal multiple access (NOMA) and Simultaneous wireless information and power transfer (SWIPT) is an emerging technology that can meet the requirements of spectral efficiency and energy efficiency. In this paper, we study the achievable rate maximization for jointly downlink and uplink network with power splitting-based SWIPT. We propose two different models. By using Single-Input Single-Output (SISO)-NOMA in conjunction with SWIPT, a joint uplink and downlink resource allocation scheme is proposed with the optimization objective to maximize the sum rate. We prove the objective function is strictly concave and found the optimal power splitting factor of each user. By using Multiple-Input Multiple-Output (MIMO)-NOMA in conjunction with SWIPT, we add timeslot allocation and propose a power splitting control and a timeslot allocation scheme. The optimization problem is divided into two subproblems to reduce solving complexity. In more detail, we first design the power splitting control scheme to maximize both the achievable rate and harvested energy in the downlink. Then timeslot optimization method is designed to improve the sum throughput. The simulation results show that a relatively high downlink rate can be achieved, while the required energy is simultaneously harvested by the users for the uplink.