This paper examines radio resource allocation in a full-duplex (FD) reconfigurable intelligent surface (RIS)-assisted wireless-powered (WP) industrial internet-of-Things (IIoT) communication network. The system model includes an FD access point (FD-AP) that communicates with FD energy harvesting (EH) mobile users (MUs), referred to as an FD-FD RIS-assisted WP-IIoT network. The FD-AP is equipped with two sets of multiple antennas: one set for downlink (DL) energy beamforming and another for uplink (UL) information signal reception. The FD-MUs have one antenna for DL energy signal reception and another for UL information transmission. This paper addresses the UL sum-rate maximization problem for the FD-FD RIS-assisted WP-IIoT system by jointly optimizing the RIS phase shift and power resources. Additionally, this paper presents two benchmarks as specific cases of the FD-FD RIS-assisted WP-IIoT system model, namely, (i) FD-HD RIS-assisted WP-IIoT network: FD AP and half-duplex (HD) two MUs groups, and (ii) HD-HD RIS-assisted WP-IIoT network: HD AP and HD MUs. The numerical results demonstrate that the FD-FD system outperforms both benchmarks in the low transmit power regime. Also, compared to the baseline non-RIS-assisted WP-IIoT network, the RIS-assisted WP-IIoT network achieved a significant UL sum-rate gain.

Integrating rate-splitting multiple access (RSMA) and reconfigurable intelligent surface (RIS) into vehicular communication systems for the Internet of vehicles (IoV) offers significant potential for enhancing quality of service, but also introduces challenges in radio resource allocation due to increased system complexity and the heterogeneous movement patterns of vehicles. In this paper, we propose an IoV communication system that leverages partitioned antenna arrays, RIS elements, and subarray-subsurface-vehicle mapping to reduce computational complexity, with RSMA serving multiple vehicles and users therein. This partitioning and mapping approach, combined with a zero-forcing technique that decouples precoding at the base station (BS) and decoding at the user equipment (UE) into a zero-forcing factor and a precoding/decoding factor, effectively mitigates inter-vehicular interference. For sum-rate maximization, we develop an alternating optimization algorithm that incorporates a dynamic partitioning scheme, which divides the BS antennas and RIS elements into subsets and maps them to individual vehicles for transmitting common and private streams to UEs therein. The passive beamforming for each RIS subsurface is optimized using the Riemannian conjugate gradient (RCG) method, while precoding at the BS subarrays and decoding at the UEs are optimized using a weighted minimum mean square error (WMMSE) approach. Simulation results and comparisons with benchmarks demonstrate that the proposed solution achieves robust system sum rate while significantly reducing computational complexity.

Ambient backscatter communication has emerged as a promising paradigm for ultra-low-power wireless systems. To support diverse IoT applications, backscatter communication should support high uplink throughput, maintain ultra-low power consumption, and reuse existing Wi-Fi signals without special infrastructure. Achieving high-throughput backscatter over existing Wi-Fi signals, however, remains challenging because rapid fluctuation of ambient signals distort the backscattered signal, severely degrading decoding reliability and limiting throughput. Existing approaches, such as codeword translation and per-sample encoding, fail to meet all these requirements, particularly due to their limited throughput caused by single-carrier modulation and the need for additional hardware, such as dual receivers or full-duplex receivers. To address this issue, in this paper, we propose MCScatter, whereby an ultra-low-power device (ULPD) modulates its data using multi-carrier modulation and transmits data by reflecting ambient Wi-Fi signals. To mitigate distortion from ambient signal fluctuations, MCScatter estimates the effective channel, capturing both wireless propagation effect and fluctuations, and equalizes the received signal accordingly. To boost throughput, MCScatter incorporates two mechanisms: Frequency-aware Adaptive Modulation (FAM), which chooses different modulation schemes across subcarriers, and Maximum Likelihood Estimation (MLE), which enables reliable decoding of ULPD data embedded on the cyclic prefix (CP) of a Wi-Fi signal. To the best of our knowledge, MCScatter is the first design to jointly realize OFDM-based ULPD modulation with practical reuse of ambient Wi-Fi signals. To analytically characterize system behavior, we develop an analytical bit error rate (BER) model for MCScatter. Evaluation results demonstrate that MCScatter significantly outperforms benchmarks in both BER and throughput.

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Backscatter communication has evolved, but the research interest has predominantly focused on a single carrier radio frequency source. In this paper, we propose a joint Repetition Coding (RC) and Multi-Source Temporal Combining (TC) framework to enhance the reliability and throughput of backscatter communication. Unlike conventional approaches that rely on a single carrier source or uniform repetition coding, our method dynamically assigns position-aware repetition codes while leveraging multiple ambient RF sources to exploit temporal diversity. We developed an analytical model to evaluate the bit error rate (BER) performance under different coding strategies and source distributions. Furthermore, we derive a closed-form optimization framework for adaptive weight allocation in TC, ensuring that the contribution of each RF source is weighted based on SNR, coherence time, and estimated BER.

In this paper, we propose a rate-splitting multiple access (RSMA) communication system assisted by multiple reconfigurable intelligent surface (RIS) devices, incorporating in-band over-the-air (OTA) control and feedback links for the RISs, and develop a corresponding radio resource allocation algorithm. To facilitate in-band OTA communication, each RIS is divided into two subsets: one dedicated to reflecting data signals from the base station (BS) toward users, and the other allocated for transmitting RIS feedback signals back to the BS. We present an alternating optimization approach that jointly optimizes the beamforming vectors at the BS and the reflection coefficients of the RISs. Specifically, our solution employs the weighted minimum mean square error (WMMSE) algorithm combined with a projection method to satisfy the RIS control rate constraints, while leveraging the Riemannian conjugate gradient algorithm for updating RIS reflection coefficients. Extensive simulation results demonstrate that the proposed scheme achieves robust and stable user sum-rate performance while effectively supporting the OTA control and feedback signaling. Additionally, the results provide insights into the impacts of RIS subset sizes, RIS control rate constraints, and BS transmit power on overall network performance.

To highlight the potential of RSMA and multicarrier (MC) techniques in vehicle-to-everything (V2X)communication, we propose and present a two-way communication MCRSMA V2X communication system that supports a large number of equipments (UEs) and promotes the dual function of sidelink and cellular communication. We employ$\mathbf{k}$-mean clustering for vehicle grouping and a suboptimal sub-carrier allocation with naive equal time and optimal precoder design for data transfer. To confirm the efficacy of the proposed system model, we compare the MC-RSMA solution against an MC-SDMA benchmark, using sum-rate as the performance metric. From the simulation results, the proposed system demonstrates significant improvements over the two multi-access technique benchmarks.

In this paper, we develop an optimization framework for the symbiotic operation of a primary multi-vehicle-to-everything (MV2X) communication network employing downlink communication and a secondary backscatter (BC) communication (BackCom) network of wireless-powered sensor equipped reflecting configurable surfaces (RISs), sharing the same spectrum. The secondary semi-passive RISs provide the multiple primary receivers with a spatial diversity gain and enable transmitting their own data to a designated IoT central system equipped with a BC reader. We develop an alternating optimization algorithm for resource allocation to maximize the sum-rate for mutually beneficial symbiotic radio operation. The presented simulation results demonstrate the superiority of the proposed optimization algorithm over conventional beamforming designs and fixed RIS reflection coefficient benchmarks.

Symbiotic radio networks (SRN) have gained traction for efficient spectrum usage in wireless communication Internet-of- Things networks (IoTNs) applications. Furthermore, the efficient use of energy resources under energy-efficient communication is rising in IoTNs to satisfy and attain the United Nations' sustainable development goals on sustainable and renewable energy usage. Hence, this work focuses on energy and spectrum efficient usage through renewable radio frequency (RF) energy harvesting (EH) backscatter (BC) communication (BackCom) and SRN between a secondary network sensor-equipped EH intelligent reflective surface BC and a primary network base station to multiple user equipment using multiple access communication. This work focuses on resource allocation optimization to maximize the system energy-efficiency quality-of-service for the SRN. The superiority of the proposed scheme over existing benchmark schemes is also presented in this work.

As the capabilities for vehicular communications have become widespread, periodic beaconing is becoming fundamental to tracking neighbors. Specifically, a vehicle periodically broadcasts its kinematic data and receivers estimate the sender’s evolving position. To ensure safety, tracking neighbors via beaconing requires position errors and transmission delay to be small. To satisfy stringent requirements, previous proposals have employed multiple RF devices based on the unrealistic assumption that vehicles have the same type of RF devices. In reality, vehicles possess different RF devices (heterogeneous vehicle conditions). Satisfying the requirements under heterogeneous conditions is challenging because network connectivity is low and multi-hop transmissions to improve the connectivity aggravate network congestion. To address this challenge, we propose a novel scheme using a model-based trajectory prediction and multi-hop transmissions adaptively. To maintain accuracy of the model, each vehicle creates a model for predicting its own trajectory and distributes the model. For reliable multihop transmissions, our scheme employs periodic scan for translator and disconnected neighbors (PSTN) and probabilistic relay (PR). To our knowledge, this is the first to consider heterogeneous vehicle conditions for tracking neighbors via beaconing. Evaluation confirms that our scheme tracks neighbors more accurately than previous work.

Wireless virtual reality (VR) that offloads VR processing to a powerful PC and streams rendered VR image frames to a VR headset wirelessly is a promising technology for high-quality interactive VR experiences with free mobility and high immersiveness. Realizing wireless VR in IEEE 802.11 WLANs is feasible when combined with the Timewarp technique, but minimal latency is still of importance for higher quality of VR service. In this paper, we reveal that the bi-directional transmission nature of wireless VR (VR frame data in downlink and motion-feedback data in uplink) and the resulting delay of motion feedback is a major challenge of wireless VR in IEEE 802.11 WLANs. To combat this challenge, we propose three basic methods-(1) prioritizing aged motion data, (2) using reverse direction, and (3) limiting the aggregation size of downlink transmission-and demonstrate that all enhance the latency and jitter of motion feedback, and, among these, limiting the aggregation size is most effective. We then design a scheme to adjust the aggregation size of downlink transmission in conjunction with the use of reverse direction to best support responsive and frequent motion feedback while preserving the downlink transmission of VR frame data.

Reliable safety message dissemination is a fundamental primitive for constructing intersection safety systems. Normally, the dissemination is based on vehicular communications, of which the de-facto standard is Dedicated Short Range Communications (DSRC). However, due to high frequency operations, a DSRC signal is seriously attenuated when being propagated in Non Line-Of-Sight (NLOS) conditions. Previous schemes leveraged the use of centralized infrastructures or relay vehicles enabling a safety message to bypass large obstacles. However, implementing the infrastructures in all intersections would be very costly; one may not find proper relay vehicles in low density, and frequent rebroadcasts cause serious network congestion in high density. To address this challenge, we propose a novel scheme that exploits excellent propagation characteristics of a TV White Space (TVWS) band (in addition to a DSRC band) for reliable dissemination in NLOS intersections. To ensure reliable dissemination throughout a broad range of densities without infrastructures, our scheme employs two innovative mechanisms: a collaborative procedure and a Dynamic optimal Configuration (DoC). To our knowledge, this is the first that simultaneously satisfies two vital demands for intersection safety system: 1) lacking infrastructures and 2) working well in all densities. Simulation studies show that the proposed scheme outperforms previous infrastructure-based schemes.

The concurrent use of multiple Wi-Fi radios in individual frequency channels is a solution readily available today to the increase of a mobile station's communication capacity, but at the expense of occasional performance deterioration (when the heterogeneity of capacity between interfaces gets severe) and additional power consumption. This paper proposes a mobile-side solution for the concurrent use of multiple radios in a performance-aware and energy-efficient manner, with which a mobile station activates and deactivates radio interfaces dynamically according to traffic demands and a predicted capacity gain. To this end, the proposed solution is composed of multiple prediction algorithms and a control algorithm. Prediction when activating an additional radio interface is relatively difficult since no information of the disabled interface's current status (and the corresponding frequency channel's) is available at the time of prediction. Our experiments show that, despite different types and used channels, different radio interfaces have a strong correlation of received signal strengths and used PHY rates between them. Based on this observation, the proposed solution learns a correlation pattern between interfaces whenever multiple interfaces are active and makes prediction of the coverage, expected PHY rate and capacity impact of an inactive interface based on the learned correlation with a currently active interface. The design of the prediction algorithms are based on a simple or machine-learning technique (SVM). The control algorithm then keeps monitoring the utilization of active interfaces and, if any of them has utilization over a threshold, checks if each inactive interface is within coverage and a valid rate range based on an active interface's received signal strength. Finally, an action of a configuration change (either activation, deactivation, or no change) selected based on the prediction of the resulting capacity is applied. Testbed experiments using COTS dual-band Wi-Fi interfaces demonstrate that the solution can enhance throughput by up to 29.6 percent (in a close distance to AP) and at most halve power consumption compared to legacy aggregation while the gain varies depending on the location and traffic conditions.

Full-duplex communication is drawing high attention as a means of enhancing wireless capacity considerably by enabling simultaneous transmission and reception on the same frequency spectrum. While it had been considered infeasible for a long time due to strong self-interference, recent researches have made substantial progress on addressing this challenge. This paper focuses on designing full-duplex cellular networks with co-channel femtocells. Due to relatively high transmit power, cancellation of self-interference by existing techniques could still be imperfect for cellular systems and thus residual interference may impact performance significantly. To overcome this in OFDMA systems, a new radio resource management scheme assigning downlink and uplink transmissions jointly while considering the gain of self-interference cancellation is developed. Three available transmission modes of a frequency resource block and crossover points between their achievable capacities are identified for the mode selection of each resource block. Users are then assigned resource blocks and transmit power levels are determined such that the total utility sum is maximized. To handle new femtocell interference scenarios, the transmit powers of femtocells and their connected users are adjusted by a coordination algorithm such that both data transmission and mode selection of an underlying macrocell are protected.

In wireless networks, broadcasting is a fundamental communication primitive for network management and information sharing. However, in multi-channel networks, the broadcast efficiency is very poor as devices are distributed across various channels. Thus, a sender tries all channels for broadcasting a single message, which causes large overhead. In this paper, we propose a novel scheme for efficient broadcast in multichannel networks. Our scheme leverages the overlapped band, which is the frequency range that partially overlapped channels (i.e., adjacent channels) share within their channel boundaries. Specifically, a sender advertises the rendezvous channel through the overlapped band of adjacent channels; the message sharing via broadcast is done on the rendezvous channel. Our scheme employs Signaling via Overlapped Band (SOB), which defines a new signal processing mechanism for communication via the overlapped band. SOB is integrated with MAC layer mechanisms: 1) Reserve Idle Spectrum Fragment (RISF) to reduce waiting time, 2) Reinforce Switch Notification (RSN) to reduce the residing time at a wrong channel, and 3) Multi-sender Agreement on Rendezvous CHannel (MARCH) to support multisender broadcasts. We implemented our scheme on the SORA platform. Experiment results validated communication through the overlapped band. Intensive simulation studies showed that our scheme drastically outperformed previous approach.

To achieve high spatial reuse of spectrum resources with limited inter-layer/cell interference, co-channel femtocells must be coordinated with the underlying macro- and other femto-cells in using radio resources. While inter-cell signaling can coordinate femtocells by providing the status information of neighbor cells explicitly, signaling delay-which may result from a limited signaling rate to reduce the resulting overhead, network latency, etc.-and its impact on the behavior of distributed coordination has not been explored before. In this paper, we propose a new architecture for the distributed coordination of co-channel femtocells based on asynchronous inter-cell signaling, called asynchronous coordination of co-channel femtocells (ACoF). ACoF improves solutions iteratively; femtocells update radio resource usage based on the received information, which usually gets outdated due to delayed signaling and asynchronous update behavior. ACoF allows each femtocell to adjust its signaling rate depending on its local conditions for fine-grained cost minimization, but at the expense of higher degree of inconsistency of femtocells' knowledge. Despite such asynchrony and inconsistency, the solution yielded by ACoF is guaranteed to converge to a global optimum under a certain condition of configuration parameters, which we prove theoretically. We design the optimization method of per-cell signaling rate for both wired and over-the-air signaling. Finally, we present a joint muting and transmit power adjustment scheme designed for ACoF and evaluate its convergence behavior and performance gain.

In vehicular safety systems, two types of safety messages are required: Emergency Safety Message (ESM) and Periodic Beacon Message (PBM). The ESM has to be disseminated within a specified area with stringent delay and delivery ratio requirements, while the PBM does not need to meet these requirements. For exchanging the safety messages in Vehicular Ad-hoc NETwork (VANET), Inter-Vehicle Communication (IVC) is necessary whose de facto standard is Dedicated Short-Range Communications (DSRC). However, the effective transmission range in the DSRC-based IVC is short since a signal can be attenuated due to blocking by obstacles. In order to cover a large dissemination area in the DSRC-based IVC, multi-hop dissemination is required, which however causes channel collision and network congestion. Moreover, the coexistence with PBMs aggravates the collision and the congestion, which make it hard to satisfy the requirements of the ESM dissemination. To overcome the limitation of the DSRC, we utilize an extra TV White Space (TVWS) band that has a large communication range for ESM disseminations, and exploit a DSRC band for 1) the exchange of control data and 2) the compensation of ESM reception errors. In this paper, we propose and analyze a distributed channel usage framework that exploits advantages of DSRC and TVWS bands for ESM dissemination under the existence of PBMs. Our scheme employs TVWS Channel Rendezvous Algorithm (TCRA), ensuring that vehicles within a dissemination area select the same channel with the ESM sender. To compensate ESM reception failures in a TVWS band, our scheme adopts Two-Way Recovery Algorithm (TWRA) that uses DSRC and TVWS bands for ESM retransmission. Further, we establish an analytical delivery ratio model that considers a delay bound of an ESM for optimal parameter selections. To the best of our knowledge, this is the first attempt to propose a distributed channel usage scheme that leverages the strengths of TVWS and DSRC bands for safety message dissemination. Through an in-depth simulation study, we show that the proposed scheme satisfies ESM requirements for latency and packet delivery ratio, and outperforms previous approaches in various vehicular scenarios.

Heterogeneous networks (HetNets) are typified by cellular deployments with multiple types of cells of different sizes and overlapping coverage areas using a common frequency band. Especially, hotzone cells overlaid on a macrocell to cover hotspot areas are expected to prevail in HetNets, thus cost-effectively enhancing cellular capacity via spatial reuse of spectrum resource and offloading macrocells. In order to fully achieve such benefits, users need to be properly distributed/assigned to the overlaid hotzone cells such that the radio resources therein are fully utilized. To this end, we propose a new architecture called Adaptive Range Control of Hotzone Cells for Heterogeneous Networks (ARCHoN) that jointly controls the radio resource allocations and ranges of OFDMA-based hotzone cells. The use of cell ranges for distributing users in ARCHoN is advantageous in that it can be implemented within a conventional cell-selection framework without modifying user devices or an air interface. In ARCHoN, each cell allocates users radio (frequency, time and power) resources in a non-cooperative manner, deriving a sequence of allocations monotonically decreasing the entire load. For range control, two algorithms are proposed: per-cell and universal, which have a tradeoff between performance and computational complexity. The solution yielded by the combination of these radio resource and range control algorithms is analytically proven to converge to a unique fixed point. Our in-depth evaluation has shown ARCHoN to significantly improve the service quality of users; in an example simulation scenario, ARCHoN is shown to improve the signal-to-interference and noise ratios (SINRs) of users, on average, by up to 3.5 dB in downlink and 18.8 dB in uplink, over the case of the conventional handover framework.

Femtocell technology has been drawing considerable attention as a cost-effective means of extending cellular coverage and enhancing capacity as well as realizing its potential, when combined with orthogonal frequency-division multiple access (OFDMA), for improved indoor broadband wireless services. However, under the expected co-channel deployment of femto- and macro-cells, femtocells may incur high uplink interference to macrocells, and vice versa. To mitigate this interference, we propose a distributed and self-organizing femtocell management architecture, called the Complementary TRi-control Loops (CTRL), that consists of three control loops to determine (1) maximum transmit power of femtocell users based on the fed-back macrocell load margin for protection of the macrocell uplink communications; (2) target signal to interference plus noise ratios (SINRs) of femtocell users to reach a Nash equilibrium; and (3) instantaneous transmit power of femtocell users to achieve the target SINRs against bursty interference from other nearby users. CTRL requires neither special hardware nor change to the radio resource management (RRM) of existing macrocells, thus facilitating non-disruptive (hence seamless) penetration of femtocells. Also, CTRL guarantees convergence in the presence of environmental changes and delayed feedback. Our evaluation has shown CTRL to successfully preserve the macrocell users' service quality under highly dynamic user transmission conditions and be able to make a tradeoff between macrocell and femtocell capacities.

Femtocell technology has been drawing considerable attention as a cost-effective means of improving cellular coverage and capacity. However, under co-channel deployment, femtocells may incur high uplink interference to existing macrocells, and vice versa. To alleviate this interference, we propose a distributed and self-organizing femtocell management architecture, called CTRL Complementary TRi-control Loops), that consists of three control loops. First, for protection of macrocell users' uplink communications, CTRL controls the maximum TX power of femtocell users based on the fedback macrocell's load margin so as to keep, on average, the macrocell load below a certain threshold. Second, CTRL determines the target SINRs of femtocell users, conditioned on the maximum TX power, to reach a Nash equilibrium based on their utility functions, thus achieving efficient coordination of uplink usage among femtocells. Third, for protection of femtocell users' uplink communications, the instantaneous TX power of each femtocell user is controlled to achieve the target SINR against bursty interference from nearby macrocell or femtocell users.

This paper presents a new two-step mathematical model which analyzes the throughput of the IEEE 802.11 distributed coordination function (DCF) with the automatic rate fallback (ARF) rate adaptation algorithm. First, the ARF algorithm is modeled as a discrete-time Markov chain and, from the Markov chain, the station distribution among physical rates is obtained. Then, it is fed to the DCF throughput model which takes the backoff mechanism into account. This two-step approach simplifies the overall model by separating the ARF algorithm and the backoff mechanism in modeling.

In this paper, we present an accurate throughput model of the IEEE 802.11e enhanced distributed coordination function (EDCF). Compared to the previous models, we newly consider a delay bound by predicting an effective retry limit and applying the retry limit to our model. To support this, the accurate description of the performance in a non-saturation condition is necessary, which is achieved by newly considering a queue length and a queue limit in the Markov chain. Simulation results show that our model is accurate in predicting the system throughput.

As a radio access technology for next generation cellular networks, 3GPP and 3GPP2 are standardizing long term evolution (LTE) and ultra mobile broadband (UMB), respectively. In this paper, we compare the handover schemes of both technologies in three aspects, i.e., interruption time of a user plane, required wireless resources and the overhead for avoiding packet reordering. The comparison results show that UMB achieves shorter interruption time and less overhead for reordering avoidance while LTE incurs less resource waste.