This paper investigate an unconventional integration of integrated sensing and communication (ISAC) with mobile broadband ultra-reliable low-latency communication (mBRLLC). Specifically, a dual-functional radar-communication access point (DFRC-AP) with extremely large aperture arrays (ELAA) serve multiple communication nodes and perform near-field radar sensing while meeting strict URLLC requirements. Unlike conventional works focusing on rate maximization or latency-reliability trade-offs, the prime objective is to maximize the worst-case achievable rate while considering sensing and block-length constraints. A hybrid beamforming design problem is formulated which is solved using a sub-optimal alternating optimization (AO) framework, combining convex approximations and manifold optimization. Extensive simulations demonstrate fast convergence and robust performance under varying system parameters, showcasing the potential of the proposed framework to improve communication and sensing efficiency in next-generation networks. The results demonstrate that hybrid beamforming offers a optimal trade-off between communication and sensing performance with improved computational efficiency and hardware cost when comapred to fully-digital precoding. Moreover, the near-field considerations enhances sensing and mBRLLC performance with more users.

This work investigates a multihop multirelay network in which all nodes are of the battery-assisted (BA) energy harvesting (EH) type, and harvest energy from a power beacon. In each hop, the node with the most harvested energy is selected for relaying and augments the harvested energy with some battery energy. Note that such BA EH nodes are immediately realizable to prolong battery lifetimes. Considering nonlinear EH, analytical expressions are derived for outage probability, throughput, average battery energy consumption, and battery energy efficiency (BEE). It is first shown how the parameters can be chosen to maximize the network throughput. Since unsuccessful relaying that results in outage causes battery energy to be consumed, optimizing the network to minimize the average battery energy consumption or to maximize the node-level BEE is well motivated. We show that the judicious selection of the EH duration can minimize average battery energy consumption while achieving the target throughput requirement. Moreover, a joint optimal choice of EH duration, hop count, and target information rate is shown to maximize overall BEE. Monte Carlo simulations validate the accuracy of the derived expressions.

This paper investigates a cooperative Internet of Things (IoT) non-orthogonal multiple access (NOMA) network comprising of a multi-antenna base station (BS), a near IoT user (NU) with full-duplex capabilities, and multiple far IoT users (FU). The NU utilizes the power-splitting (PS) energy harvesting (EH) protocol and augments the harvested energy with a little energy from its battery to assist the FU. Considering the novel cooperative NOMA/non-cooperative (C-NM/NC) switching, the impact of successive interference cancellation (SIC), channel state information (CSI) errors, and nonlinear EH, closed-form expressions are derived for average blocklength error rates (BLER) of both users in finite blocklength regime. Utilizing the derived BLER expressions, the Goodput, Reliability, Latency, and battery power efficiency are expressed in closed form. We then demonstrate that the CSI errors severely degrades the performance of both the users. Monte Carlo simulations validate the accuracy of the derived analytical expressions. We also establish that a significantly better maximum performance is attained at the FU, given a target NU Goodput by the careful choice of NOMA and EH parameters. C-NM/NC switching offers a higher EE and better self-interference immunity. Results indicate that the choice of blocklength is crucial for efficient system performance.

In this work, we consider a cooperative communication network wherein a base station (BS) utilizes a simultaneous wireless power and information transfer (SWIPT) energized full duplex-decode and forward relay to communicate with a downlink user. The relay augments the harvested energy with a bit of energy from its battery. Assuming a practical nonlinear energy harvesting (EH) model, we derive approximated closed-form expressions for the end-to-end blocklength error rate (BLER) under the finite blocklength (FBL) regime for both power splitting (PS) and time switching (TS) protocols. We then derive a high-SNR approximated expression for end-to-end BLER to demonstrate the interplay of the battery energy, blocklength, and EH parameters on the system’s performance. We also analytically establish the convexity of the BLER with respect to the relay’s battery energy. Using the expression for the BLER, we derive expressions for the goodput and battery energy efficiency in approximated closed-form. Moreover, for a desired target BLER requirement, we show that, by carefully choosing the TS/PS parameter, the required relay’s battery energy can be minimized. The accuracy of the derived analytical expressions is validated using Monte Carlo simulations. Finally, we discuss the impact of key parameters such as transmit power, total available blocklength, nonlinear EH, TS, and PS parameters, and battery energy on the network’s performance.

This paper investigates the delay performance of a battery-assisted (BA) multi-hop cluster-based network assuming that each hop consists of multiple relays. At each hop, all the nodes harvest energy from the power beacon utilizing the time-switching (TS) energy harvesting (EH) protocol, and augment it with limited energy from a battery in a battery-assisted EH framework. Note that such BA EH nodes are immediately realizable and can prolong battery lifetimes. For efficient relay's battery utilization, the relay with successful decoding status and the largest amount of the harvested energy is selected for forwarding the information in each hop. The symbols are retransmitted after energy harvesting if an acknowledgment is not received from at least one node in the next hop. Considering saturation-based nonlinear EH, an expression is derived for the average delay performance. We then demonstrate that the average delay can be minimized by optimal selection of the TS parameter. Our results also demonstrate that augmenting the harvested energy with a small amount of battery energy dramatically improves the average delay performance. In view of the explosion in number of machine-type devices (MTDs) in recent times, such analysis is of immense practical importance. Monte Carlo simulations validate accuracy of the derived expressions.

This article investigates a cooperative nonorthogonal multiple access (Co-NM)-based network consisting of a multiantenna source, a full-duplex energy harvesting (EH) near user (NU) Internet of Things (IoT) node, and multiple distant user (DU) IoT nodes. The source shares a direct link to the NU, while the NU augments the harvested energy by a limited amount of its battery energy to relay the information to the selected DU. Considering time-switching (TS) or power-splitting (PS) protocol, practical nonlinear EH, successive interference cancellation error, and opportunistic Co-NM/orthogonal multiple access (OMA) (OM) switching, closed-form expressions are derived for the outage probability and throughput of both DU and NU. We demonstrate that the proposed opportunistic Co-NM/OM switching can ensure a performance similar to OM at the NU without loss in DU throughput. Also, a joint optimal choice of battery energy and PS/TS parameter helps in attaining a maximum energy efficiency (EE). Moreover, Co-NM/OM switching ensures higher EE as compared with Co-NM and OM.

This paper investigates the performance of an uplink multiuser IoT network in which green self-sustaining IoT users utilize the energy harvested from the downlink signal for uplink signalling using NOMA principles. The uplink user with best link signal-to-noise (SNR) is first chosen. To increase spectral efficiency, another user is also picked for concurrent transmission using non-orthogonal multiple access (NOMA) principles. We demonstrate that the choice of the second user depends on the target rate and number of users, and is not always the user with the second-best SNR. The users are selected using a timer-based mechanism, and no feedback of channel estimates is involved. Considering the time-switching protocol for energy harvesting, we obtain expressions for outage probability and throughput of this scheme. Unlike in traditional uplink NOMA networks, the transmit powers here are random, and this makes the analysis and user selection mechanism interesting. Accuracy of the derived expressions is illustrated by computer simulations.

In this paper, a new instantaneous channel state information-based dynamic time-switching (TS) energy harvesting (EH) protocol is proposed for a two-hop battery-assisted full-duplex (FD) relay network. To ensure reliable communication, a quantum of the battery energy augments the harvested energy. Assuming nonlinear EH, performance is evaluated in terms of throughput for static TS and dynamic TS protocols. In such networks, node-level energy considerations are clearly important but have not attracted research attention. It is demonstrated that by jointly optimizing the average battery energy consumption and the TS parameter, the throughput for both static and dynamic TS protocols can be maximized. It is also demonstrated that the proposed dynamic TS protocol provides substantial gains in throughput and average energy savings compared to the static TS protocol. The accuracy of the derived analytical expressions is verified through Monte Carlo simulations.

This paper investigates the performance of a time-switching (TS) based cooperative non-orthogonal multiple access (NOMA) network consisting of a base station (BS), a near user (NU), a distant user (DU), and a full-duplex (FD) relay. The BS shares a direct link to the NU, while communication to the DU is assisted by a battery-aided energy harvesting FD relay. We consider a static battery energy (SBE) scheme in which a fixed amount of battery energy augments the harvested energy and analyze the performance of both NU and DU. Also, a new dynamic battery energy (DBE) scheme, wherein the harvested energy is augmented with as little battery energy as possible in order to achieve desired quality of service, is proposed and is shown to ensure efficient battery utilization. Considering a threshold-based nonlinear EH model, closed-form expressions are derived for the throughput of NU and DU for both SBE and DBE schemes. Furthermore, for the DBE scheme, we also derive an exact closed-form expression for the average battery energy drawn per symbol interval. We then demonstrate that the choice of battery energy and TS parameter is crucial to attain a maximum DU throughput while simultaneously guaranteeing a target throughput at the NU.

In this work, we investigate rate-splitting multiple access (RSMA) for a multiuser downlink wireless network consisting of an unmanned aerial vehicle (UAV)-assisted base station (BS) that serves multiple ground users (GUs) simultaneously. Considering two different transmission regimes, namely infinite blocklength (IBL), and finite blocklength (FBL), we analyze the performance of the considered network under the effect of imperfections in channel state information (CSI) estimation and successive interference cancellation (SIC) with the probabilistic line of sight fading channels. For IBL transmission, we derive the closed-form expressions of the outage probability, throughput, and achievable ergodic rate at each GU. Furthermore, for short packet communication, the closed-form expressions of block error rate (BLER), goodput, and achievable ergodic rate are determined with FBL transmission. Moreover, for the FBL regime we also formulate an optimization problem that jointly optimizes the 3D-position of the UAV, power allocated to each user, and common rate distribution at each user to maximize the ergodic sum rate subject to the practical constraints such as maximum tolerable BLER, minimum private and total rate at each user. We then propose an alternating optimization-based iterative algorithm to solve the problem. Monte-Carlo simulations are used to verify the accuracy of derived analytical results and demonstrate the trade-off between transmit power and achievable BLER. In addition to this, the effectiveness of RSMA in UAV-assisted communication under IBL and FBL transmission regimes is also observed compared to non-orthogonal multiple access.

In this work, we consider a hybrid aerial full-duplex (FD) relaying consisting of a reconfigurable intelligent surface (RIS) mounted over an FD unmanned aerial vehicle (UAV) relay operating in decode and forward mode to assist the information transfer between the base station and multiple users. For better spectral efficiency, we investigate the use of rate splitting multiple access (RSMA) in such networks and focus on joint optimization of RSMA parameters, 3D-coordinates of the UAV/RIS, and phase shift matrix at the RIS along with analyzing the outage probability, block error rate (BLER) and achievable weighted sum rate for finite blocklength (FBL) and infinite blocklength (IBL) codes under imperfect successive interference cancellation (SIC) at each user and residual-self interference (RSI) at the UAV. We first formulate the weighted sum rate maximization problem and adopt the block coordinate descent (BCD) method to deal with the non-convex nature of the problem. Thereafter, we propose a BCD-based algorithm that jointly optimizes these parameters using a heuristic approach for optimum power allocation, a Riemannian conjugate gradient-based algorithm to get the optimal phase shift at the RIS, and an iterative algorithm to obtain the optimal UAV/RIS position. It also distributes the common rate among the users optimally. Next, with obtained optimal parameters, we further analyze the performance of the network and derive the closed-form expressions of BLER, outage probability, and average weighted sum rate. We present Monte Carlo simulation-based results to validate the accuracy of the proposed algorithms and derived expressions, and demonstrate the superiority of RSMA over non-orthogonal multiple access (NOMA) and conventional orthogonal multiple access (OMA) schemes.

This paper investigates the performance of a new framework for low-outage downlink non-orthogonal multiple access (NOMA) using a coordinated direct and relay transmission (CDRT) scheme with direct links to both the near-user (NU) and the far-user (FU). Both amplify-and-forward and decode-and-forward relays are considered. In this framework, the NU combines the signals from base-station and relay at each stage of the successive interference cancellation (SIC) to attain good outage performance. For both NU and FU, the expressions for outage probability and throughput are derived in closed form. We also derive the high-SNR expressions for the outage probability to demonstrate that with the proposed framework, both users harness a diversity of two without feedback bits (this is the only framework to achieve this). We demonstrate that the choice of power allocation coefficient and target symbol rates is crucial to maximizing the NU throughput while ensuring a desired target FU throughput. We demonstrate that CDRT with the proposed framework outperforms known schemes in terms of outage probability, sum throughput, and energy efficiency. Moreover, we also show that optimal rate selection is important to maximize the energy efficiency. Monte Carlo simulations validate the accuracy of the derived analytical expressions.

Owing to the factors such as controllable mobility, ready-to-use technology, low cost, easy implementation, and so on, unmanned aerial vehicle (UAV) possesses tremendous potential to be one of the primary candidates for next-generation (6G) wireless networks. This paper presents a UAV-assisted multiuser communication network where a multiple antenna UAV base station (BS) serves multiple single antenna ground users (GUs). UAV-BS uses a laser source-based charging mechanism to fulfill its power requirement and applies simultaneous wireless information and power transfer (SWIPT) in the downlink in order to provide desired power to energy-constrained GUs. Also, a clustering-based hybrid multiple access technique is used that combines both orthogonal multiple access (OMA) and non-orthogonal multiple access (NOMA) signaling to transmit the information to all GUs, simultaneously. Due to the involved analytical complexity corresponding to the multiple antennas and users, we use a hybrid beamforming method for efficient communication. Next, we analyze the performance of the proposed framework in terms of user outage probabilities, their respective throughput, and average power harvested considering non-linear energy harvesting and derive expressions of these performance metrics. Moreover, we formulate an optimization problem where the throughput of one GU is maximized by optimally choosing the power allocation parameter while ensuring the desired target throughput at other GU in each cluster. We also illustrate how crucial is the optimal selection of the target rates to maximize the network performance. Simulation results are provided to validate the accuracy of derived expressions and to highlight the dominance of hybrid beamforming and hybrid NOMA compared to conventional methods on the performance of the considered network.

In this work, we consider a hybrid aerial full-duplex (FD) relaying protocol consisting of a reconfigurable intelligent surface (RIS) mounted over an FD unmanned aerial vehicle (UAV) relay operating in the decode and forward mode to assist the information transfer between the base station and multiple users. For better spectral efficiency, we investigate the use of non-orthogonal multiple access (NOMA) in such networks and focus on both the performance analysis and design optimization of the considered RIS-NOMA network under imperfect channel state information (CSI) and successive interference cancellation (SIC) at each user, and residual-self interference (RSI) at UAV. We first formulate the sum rate maximization problem and adopt the block coordinate descent method to deal with the non-convex nature of the problem. Thereafter, we propose an algorithm based on the Riemannian conjugate gradient method to get the optimal phase shifts at the RIS, an iterative algorithm to obtain the optimal UAV/RIS position and the exhaustive method to obtain the optimum power allocation coefficients. Next, with obtained optimal position, phase shift and power coefficients, we further analyze the performance of the network and derive the closed-form expressions of outage probability, achievable throughput and ergodic capacity. We present Monte Carlo simulation-based results to validate the accuracy of the proposed algorithms and derived expressions and demonstrate the superiority of NOMA over OMA.

This paper investigates the performance of a new coordinated direct and relay transmission (CDRT) NOMA framework in which a base station (BS) communicates directly to a near user (NU), and through an amplify-and-forward (AF) relay to a far user (FU). In the first signaling phase, the BS transmits superposed symbols to both NU and relay (R), whereas in the second phase R amplifies and re-transmits the signal from the BS. In this framework, the NU optimally combines the signals from BS and R, which gives it a significant performance advantage, and allows it to harness a diversity of two. This serves as an incentive to NU to participate in NOMA signalling to assist the FU. We derive closed form expressions for the outage probability and throughput of NU and FU. We elaborate on how the power allocation and target rates can be optimally chosen so as to maximize the NU throughput while ensuring a desired FU throughput. Computer simulation results validate the improved energy efficiency of the scheme and accuracy of the derived expressions.

This paper investigates a cooperative non-orthogonal multiple access (C-NOMA) network consisting of a base station (BS), a far user (FU) and a full-duplex (FD) near user (NU). The NU does not use its own battery energy to relay to FU, and harvests energy using SWIPT principles from the BS. In this paper we consider a more practical nonlinear energy harvesting model for the first time in such a framework. We show that use of the idealized linear EH model leads to gross over-estimation of FU performance. Considering the time-splitting (TS) energy harvesting (EH) protocol, and modelling the self-interference at the FD NU, expressions are derived for the FU and NU outage probabilities in closed-form. Further, we show that by optimal selection of the TS parameter performance of FU can be further enhanced. Computer simulations confirm the accuracy of the derived analytical expressions.

In this work, we investigate an unmanned aerial vehicle (UAV)-aided novel hybrid wireless communication network consisting of a cellular user and a small internet of things (IoT) network having one low-power IoT hub which serves a sensor node. During the first signalling phase, the UAV-assisted base station (BS) uses non-orthogonal multiple access signalling to serve the cellular user and the IoT-hub, simultaneously. In the second phase, the cellular user uplinks the control signal to UAV-BS, whereas, at the same time the IoT-hub communicates with the sensor node using the power harvested by applying simultaneous wireless information and power transfer (SWIPT) and nonlinear energy harvesting. We derive the closed-form expressions of the achievable ergodic capacity of the cellular user and the IoT-hub during the first signalling phase and the sensor node and the UAV-BS during the second phase considering nonlinear energy harvesting at the IoT hub. Further, we demonstrate the trade-off between available transmit power at UAV-BS, IoT-hub (harvested power), and cellular user to achieve desired capacity at the sensor node and UAV-BS. We validate the accuracy of derived expressions by using numerical simulations.

In this paper, a coordinated direct and relay transmission (CDRT) based cognitive underlay downlink nonorthogonal multiple access network is considered, in which the source serves the near user (NU) directly while a dedicated relay assists the communication to the far user (FU). To ensure good performance in a power-constrained underlay scenario, NU combines (along with successive interference cancellation) the signals from the source and the relay in this unique CDRT framework. The secondary transmitter transmits with controlled power to ensure that the interference is below the interference temperature limit of the primary user. NU and FU performance is analyzed in terms of their outage probability and throughput in closed-form. Furthermore, we investigate how the choice of target rates and power allocation parameters is crucial to attaining the best performance. Extensive computer simulations are provided to validate the accuracy of the derived results.

This paper investigates the performance of full-duplex (FD) communication between two power beacon-assisted energy harvesting (EH) nodes. The proposed system consists of a power beacon (PB) and two FD nodes. Assuming the time-switching (TS) protocol for EH, both nodes first harvest the energy from the PB and then use this energy for information transmission. Closed-form expressions are derived for the terminal outage probabilities and the sum throughput. Further, using an asymptotic expression for the terminal outage probability, we present a closed-form expression for the TS parameter that maximizes the sum throughput. Computer simulation results demonstrate accuracy of the derived expressions.

This paper investigates the performance of a two-hop decode-and- forward full duplex relaying (FDR) network with a battery-assisted energy harvesting (EH) relay. We consider a practical scenario where the EH relay uses a limited amount of battery energy along with the harvested energy to enhance communication between the source and destination terminals. Utilizing time splitting (TS) protocol for EH, we analyze the performance of a dual-hop FDR system in terms of outage probability and throughput. Further, with fixed battery energy availability, we present closed-form expressions for the TSR parameter that maximizes throughput. For a desired target throughput, we show how the battery energy drawn and the TSR parameter can be chosen so as to extend battery lifetime. Computer simulation results demonstrate accuracy of the derived expressions.