Effective Capacity Research Articles

Effective capacity of STAR-RIS assisted RSMA network with imperfect SIC

The proliferation of various Internet of Everything applications places urgent demand for high energy efficiency, massive connection and wide coverage for the future communication era. Motivated by this, rate-splitting multiple access (RSMA) and simultaneously transmitting and reflecting reconfigurable intelligent surface (STAR-RIS) has attracted wide publicity from industry and academia. In this paper, we consider a STAR-RIS assisted two-user RSMA network with imperfect successive interference cancellation, and all channels are modeled as Nakagami-m distribution. By adopting effective capacity (EC) as the metric, we analyze the system performance under certain quality-of-service constraint. Specifically, analytical expressions of EC for a pair of RSMA users are provided. To explore further insights, high signal-to-noise ratio (SNR) conditions are also considered. Furthermore, the effect of some specific elements on system EC performance are analyzed, and some significant conclusions are obtained as follows: (1) As SNR grows, the effective capacities of two users improve, but finally converge to constant at high SNR. (2) The increase in the amount of the STAR-RIS elements can obviously increase the effective capacities. (3) Compared to traditional STAR-RIS assisted non-orthogonal multiple access networks, STAR-RIS assisted RSMA network has distinct advantages to improve system EC performance.

On The Effective Capacity Performance Analysis Over Nakagami‐m Distribution‐Based Double‐Shadowed Rician Fading Channel

AbstractThe practical applications within the domain of the fifth generation (5G) and the emerging beyond 5G network necessitate a high data transmission rate along with minimal achievable delay. With this objective in focus, the maximum capacity is extensively quantified through the utilization of the delay‐constrained effective capacity (EC) technique, which stands in contrast to Shannon's ergodic capacity. The current study is engaged in the analysis of EC within a delay‐limited wireless system operating in a double‐shadowed Rician (DSR) fading channel. Within this channel, only the Nakagami‐m distribution concept has been applied to both the dominant and secondary shadowing components of the proposed network model. A new exact closed‐form expression for EC within the DSR fading channel has been derived using the Fox‐H function. Furthermore, an analysis has been conducted for both high and low signal‐to‐noise ratios to provide further insights and explanations for the proposed model. It is worth noting that the results obtained from both simulation and analytical methods exhibit substantial similarity, revealing interdependence among various parameters present in the proposed model.

Effective capacity of rate-splitting multiple access with channel estimation errors

In view of its advantages to adeptly reduce interference and low complexity, rate-splitting multiple access (RSMA) is emerging as an innovative framework for the next generation of the wireless communication networks. In this paper, we conduct the performance analysis of a two user RSMA network under delay constrains, taking channel estimation errors into account as well. Utilizing the effective capacity (EC) as our metric, we investigate the effects of delay on a pair of RSMA users. Specifically, we derive analytical expressions for the EC concerning both the near user (SRn) and the far user (SRf). Additionally, we offer asymptotic results under high signal-to-noise ratio (SNR) conditions. From our analysis, several noteworthy conclusions can be drawn and outlined below: (1) The effective capacities (ECs) of SRn and SRf exhibit improvement with SNR increasing, while at high SNR, the ECs of SRn and SRf converge to the constants. (2) Compared to the non-orthogonal multiple access, the considered RSMA network exhibits superior EC performance due to its inherent advantages in interference management. (3) The presence of channel estimation errors adversely affects EC performance of RSMA networks, with this impact being more pronounced in the high SNR regime.

The Present Functions and the Future Persistence of Planning Agency

ABSTRACTFollowing Bratman, I distinguish between the Cummins or component‐function of the planning capacity (its role as a component of larger forms of practical organizations) and its Wright or existence‐function – the planning capacity's effect that explains its existence. I agree with Bratman that these functions are distinct. The planning capacity's role within larger practical organizations need not explain its origin. But I argue that the distinction is less stark for future‐oriented existence‐functions, which concern the future persistence and stability of the capacity. In mature practical organizations, component‐functions usually give rise to matching future‐oriented existence‐functions, given that pressures for the persistence of practical organizations transfer to their components (such as the planning capacity) because of their component‐functions. But in the special case of individual temporally extended agency, there is an even stronger alignment of functions. The planning capacity and individual temporally extended agency are part of an inextricable package. The capacity is not just a distinct component. This entails that, within individual agency, the two functions merge and the planning capacity is the primary rather than the derivative target of pressures of persistence, care, and value. Or so I speculatively conjecture.

State Capacity and COVID-19: Targeted versus Population-Wide Restrictions

Context: During the COVID-19 pandemic, governments varied in their implementation of social distancing rules. Some governments were able to target their social distancing requirements toward specific segments of the population, whereas others had to resort to more indiscriminate applications. This article will argue that state capacity crucially affected the manner in which social distancing rules were applied. Methods: Using data from the Oxford COVID-19 Government Response Tracker, the author performed a series of ordered logistic regressions to examine whether state capacity increased the likelihood of more targeted applications of each social distancing rule. Findings: Given the same level of infectivity, more capable states were indeed more likely to resort to targeted applications of each social distancing restriction. Interestingly, the size of state capacity's effect varied by the type of restriction. State capacity had a stronger influence on face-covering requirements and private-gathering restrictions than it had on school closures, workplace closures, and stay-at-home orders. Conclusions: The way in which social distancing rules are applied is endogenous to state capacity. Effective governance is a precursor to more targeted and nuanced applications of social distancing rules.

Cross Layer Resource Allocation in H-CRAN With Spectrum and Energy Cooperation

5G and beyond wireless networks are the upcoming evolution for the current cellular networks to provide the essential requirement of future demands such as high data rate, low energy consumption, and low latency to provide seamless communication for the emerging applications. Heterogeneous cloud radio access network (H-CRAN) is envisioned as a new trend of 5G that uses the advantages of heterogeneous and cloud radio access networks to enhance both spectral and energy efficiency. In this paper, building on the notion of effective capacity (EC), we propose a framework in orthogonal frequency division multiple access (OFDMA)- non-orthogonal multiple access (NOMA) based H-CRAN to meet these demands simultaneously. Our proposed approach is to maximize the effective energy efficiency (EEE) while considering spectrum and power cooperation between a macro base station (MBS) and radio remote heads (RRHs). To solve the formulated problem and to make it more tractable, we transform the original problem into an equivalent subtractive form via Dinkelbach algorithm. Afterward, the combinational framework of distributed stable matching and successive convex algorithm (SCA) is then adopted to obtain the solution of the equivalent problem. Hereby, we propose an efficient resource allocation scheme to maximize energy efficiency while maintaining the delay quality of service (QoS) requirements for all users. The simulation results show that the proposed algorithm can provide a non-trivial trade-off between delay and energy efficiency in OFDMA-NOMA based H-CRAN systems in terms of EC and EEE and the spectrum and power cooperation improves EEE of the proposed network. Moreover, our proposed solution complexity is much lower than the optimal solution and it suffers a very limited gap compared to the optimal method.

ENVIRONMENT CARRYING CAPACITY OF ECOTOURISM IN AEK NAULI RESEARCH FOREST, SIMALUNGUN REGENCY, NORTH SUMATERA

Currently, ecotourism has become an important industry because of its rapid development. Many tourism practices have adverse environmental impacts. Due to the increasingly destructive commercialization of the natural resources on which we depend, there are several negative impacts. Aek Nauli Research Forest (ANRF), with an area of 1,900 hectares, is one of the natural tourist destinations around the Lake Toba Tourism area managed by the Aek Nauli Research Institute for Environmental and Forestry Development (BP2LHK). The location of the study is in Girsang District, Sipangan Bolon, Simalungun Regency, North Sumatera Province. The tourist objects are natural panorama, elephant conservation education tour, and siamang animal ape park. On average, the number of visitors of ANRF on regular days is 100-300 visitors/day and on holidays reaches 300-1,700 visitors/day. The increase in the number of visitors is perceived to have an impact on environmental sustainability. This study aims to determine the capacity of the ANRF ecotourism area to accommodate the number of tourists per day simultaneously. The method used is the effective carrying capacity by Cifuentes method based on several stages of analysis, namely Physical Capacity (PCC), Real Capacity (RCC), Management Capacity (MC), and Effective Capacity (ECC). The environmental carrying capacity analysis results showed that the PCC, RCC, ECC were 26,106 visitors/day, 3,007 visitors/day, 2,505 visitors/day respectively while MC was 0.83. This value can be used to advise managers to limit visitors, particularly during peak season, in order to preserve objects and the quality of visits.

Effective Capacity Analysis of AmBC-NOMA Communication Systems

In this paper, we propose an ambient backscatter communication non-orthogonal multiple access (AmBC-NOMA) system framework and derive exact expressions for the effective capacity (EC) of two NOMA users and the backscatter device (BD). For more insights, we provide asymptotic analysis by invoking <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">high signal-to-noise ratio (SNR) slope</i> and <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">high SNR power offset</i> . The simulation indicates that: 1) the ECs of users tend to be the constants in the high SNR region while the EC of BD increases linearly with SNR; 2) comparing the ECs of two users, the EC advantage of near user is more obvious when QoS constraint is loose; 3) the proposed system yields better user fairness than the orthogonal multiple access case; 4) the EC of BD strengthens with the increase of BD’s reflection coefficient, while the ECs of NOMA users weaken.

Statistical QoS Analysis of Reconfigurable Intelligent Surface-Assisted D2D Communication

This work performs the statistical QoS analysis of a Rician block-fading reconfigurable intelligent surface (RIS)-assisted D2D link in which the transmit node operates under delay QoS constraints. First, we perform mode selection for the D2D link, in which the D2D pair can either communicate directly by relaying data from RISs or through a base station (BS). Next, we provide closed-form expressions for the effective capacity (EC) of the RIS-assisted D2D link. When channel state information at the transmitter (CSIT) is available, the transmit D2D node communicates with the variable rate $r_t(n)$ (adjustable according to the channel conditions); otherwise, it uses a fixed rate $r_t$. It allows us to model the RIS-assisted D2D link as a Markov system in both cases. We also extend our analysis to overlay and underlay D2D settings. To improve the throughput of the RIS-assisted D2D link when CSIT is unknown, we use the HARQ retransmission scheme and provide the EC analysis of the HARQ-enabled RIS-assisted D2D link. Finally, simulation results demonstrate that: i) the EC increases with an increase in RIS elements, ii) the EC decreases when strict QoS constraints are imposed at the transmit node, iii) the EC decreases with an increase in the variance of the path loss estimation error, iv) the EC increases with an increase in the probability of ON states, v) EC increases by using HARQ when CSIT is unknown, and it can reach up to $5\times$ the usual EC (with no HARQ and without CSIT) by using the optimal number of retransmissions.

Buffer-Aided Relaying in NOMA-Based MTC Networks With Finite Blocklength and Statistical QoS Constraints

Machine-type communication (MTC) is one of the main enabling technologies to support various applications with diverse quality of service (QoS) requirements. Finite blocklength transmission has great potential in meeting the strict delay requirements of delay-sensitive MTC devices (MTCDs), while also causing loss of network capacity due to the decoding error probability. Aiming at this problem, we introduce uplink non-orthogonal multiple access (NOMA) and buffer-aided relaying to assist the finite blocklength transmission with delay requirements for improving the achievable effective capacity (EC), which is defined as the maximum short-packet constant arrival rate under specific statistical QoS constraints. To solve the EC maximization problem, we derive the closed-form expression of time allocation coefficient. Then we establish a concave lower bound of EC using successive convex approximation (SCA) for power allocation of MTCDs, and formulate a non-cooperative game based distributed power allocation algorithm for relay. Furthermore, a joint time and power allocation (JTPA) algorithm is proposed to implement joint resource allocation. Simulation results show that under finite blocklength and statistical QoS constraints, adopting buffer-aided relaying can improve EC by 41.82% compared with no-buffer relaying. Moreover, the achievable EC of JTPA algorithm is only 3.12% lower than that of exhaustive search while reducing complexity.

Hop-by-hop bandwidth allocation and deployment for SFC with end-to-end delay QoS guarantees

Network function virtualization and 5G network slicing technology can provide a more resilient and manageable Internet by deploying various requests on different slices. In this paper, we propose a hop-by-hop bandwidth allocation framework for service function chains (SFCs) to guarantee delay QoS constraints of requests. A end-to-end (E2E) SFC contains multiple virtual network functions (VNFs), which is constructed as a tandem queueing system. The arrival is modeled as an interrupted bernoulli process (IBP) or two-aggregation Markov modulated bernoulli process (2A-MMBP) to represent the traffic of typical services, data or video call. And the effective bandwidth (EB) formulas for these intricate Markovian processes are derived. Then we use EB/ effective capacity (EC) theory to allocate the bandwidth for SFCs hop by hop and deduce the service probabilities of the nodes. On the basis of EB/EC bandwidth allocation, the departure process is fitted into an IBP or a MMBP and then becomes the arrival of the next hop, which is beneficial to engineering implementation. The novel delay evaluation metrics, E2E packet delay and delay violation probability, are developed to assess the performance of SFC deployment. We formulate the SFC deployment as an integral linear programming (ILP) problem with the objective of minimizing the total cost. Finally, a heuristic algorithm called hop-by-hop bandwidth allocation and SFC deployment (HBASD) is designed to solve this problem. Simulation results show that compared with the up-to-date methods, our algorithm can guarantee the QoS requirements of E2E delay for services and save resources.

Effective capacity optimization for UDN

For the ultra-dense distributed network (UDN), the intensive deployment leads to the collision problem of the unlicensed spectrum access due to the random contention access mechanism of the unlicensed spectrum, which is difficult to improve the user quality of service (QoS). Here, the wireless access process of the licensed assisted access (LAA) network is modelled as a four-state semi-Markov model. Then, the effective capacity (EC) of the UDN based on the random access is derived, and the network capacity limit under the QoS requirements in the unlicensed spectrum is given. Based on the obtained EC, two power control algorithms are proposed to maximize the EC and effective energy efficiency (EEE) respectively under the user QoS requirements. Finally, numerical results verify the accuracy of the proposed theory, and the capacity-delay domain of the UDN is given. The simulation results show that the proposed algorithms improve the EC and the EEE compared with existing classical schemes.

Performance Analysis of Dual-Hop RF/FSO Relaying Systems With Imperfect CSI

This paper proposes a unified performance analysis framework of asymmetric dual-hop radio-frequency/free-space optical (RF/FSO) transmission systems. The generalized independent and identically distributed (i.i.d.) <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$\alpha -\mu$</tex-math></inline-formula> distribution is considered for each branch in the RF link, whereas the FSO link is assumed to experience Málaga ( <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$\mathcal {M}$</tex-math></inline-formula> ) fading with pointing error impairments. With amplify-and-forward (AF) and decode-and-forward (DF) relaying, the imperfect channel state information (CSI) of both links is considered. For the considered system, we first derive exact and novel analytical expressions for the probability density function (PDF) and cumulative distribution function (CDF) of the end-to-end signal-to-noise ratio (SNR). Furthermore, we obtain key performance metrics such as outage probability (OP), average bit-error-rate (ABER), and effective capacity (EC). The important effects of channel parameters on the system are disclosed from mathematical analysis and are further validated by Monte-Carlo simulations.

Throughput Analysis of α-κ-µ Extreme/Gamma Composite Fading Channel

In this paper, we consider α-κ-µ-Extreme/gamma composite fading channel model, which is used to characterize non-linear severe fading and shadowing impairments in enclosed wireless propagation scenarios. For this model, we first obtain the probability density function (PDF) expression for the received signal-to-noise ratio(SNR). Using the derived PDF, throughput analysis is provided by deriving expressions for the average channel capacity(ACC) and effective capacity(EC) in closed-form. The derived expressions are evaluated for several values of fading and shadowing indexes to study their effect on the ACC and EC. Furthermore, asymptotic analysis of ACC and EC are carried out to show better approximation under the high and low SNR regimes.

Effective capacity analysis of reconfigurable intelligent surfaces aided NOMA network

The future sixth generation (6G) is going to face the significant challenges of massive connections and green communication. Recently, reconfigurable intelligent surfaces (RIS) and non-orthogonal multiple access (NOMA) have been proposed as two key technologies to solve the above problems. Motivated by this fact, we consider a downlink RIS-aided NOMA system, where the source aims to communicate with the two NOMA users via RIS. Considering future network supporting real-time service, we investigate the system performance with the view of effective capacity (EC), which is an important evaluation metric of delay sensitive systems. Specifically, we derive the analytical expressions of the EC of the near and far users. To obtain more useful insights, we deduce the analytical approximation expressions of the EC in the low signal-to-noise-ratio approximation by utilizing Taylor expansion. Moreover, we provide the results of orthogonal multiple access (OMA) for the purpose of comparison. It is found that (1) The number of RIS components and the transmission power of the source have important effects on the performance of the considered system; (2) Compared with OMA, NOMA system has higher EC due to the short transmission time.

Statistical QoS guarantees of a device‐to‐device link assisted by a full‐duplex relay

AbstractDevice‐to‐device (D2D) communication is a promising technique to enhance the spectral efficiency for 5G and beyond cellular networks. Traditionally, D2D communication was considered solely as communication directly between two closely‐located devices, without any support from the available network infrastructure; however, this understanding limits the advantages of D2D communication. Relay‐assisted D2D communication was later proposed to allow devices to exchange data and extend coverage via relay strategy for transmission distance extension and capacity improvements. This work aims to determine the statistical quality‐of‐service (QoS) guarantees of a D2D link assisted by a full‐duplex relay by employing a commonly used analytical tool, the effective capacity (EC). We provide a closed‐form expression for the EC of relay‐assisted D2D communication, in which both the transmitter and the relay devices operate under individual QoS constraints. We also provide an analysis of the impact of mode selection on the EC of relay‐assisted D2D. Additionally, for the mode selection, we propose a novel multiple features‐based mechanism by utilizing all the features of a wireless link. We further provide a closed‐form solution for the non‐convex calibration problem of the optimal weights for these underlying features. Finally, simulation results demonstrate how the quality of self‐interference cancellation techniques impacts the EC of the relay‐assisted D2D. The results also show that the performance of our proposed mode selection mechanism with optimal weights outperforms the traditional mode selection mechanism.

Effective Energy Efficiency of Ultrareliable Low-Latency Communication

Effective capacity (EC) defines the maximum communication rate subject to a specific delay constraint, while effective energy efficiency (EEE) indicates the ratio between EC and power consumption. We analyze the EEE of ultrareliable networks operating in the finite-blocklength regime. We obtain a closed-form approximation for the EEE in quasistatic Nakagami- m (and Rayleigh as subcase) fading channels as a function of power, error probability, and latency. Furthermore, we characterize the quality-of-service constrained EEE maximization problem for different power consumption models, which shows a significant difference between finite and infinite-blocklength coding with respect to EEE and optimal power allocation strategy. As asserted in the literature, achieving ultrareliability using one transmission consumes a huge amount of power, which is not applicable for energy limited Internet-of-Things devices. In this context, accounting for empty buffer probability in machine-type communication (MTC) and extending the maximum delay tolerance jointly enhances the EEE and allows for adaptive retransmission of faulty packets. Our analysis reveals that obtaining the optimum error probability for each transmission by minimizing the nonempty buffer probability approaches EEE optimality, while being analytically tractable via Dinkelbach's algorithm. Furthermore, the results illustrate the power saving and the significant EEE gain attained by applying adaptive retransmission protocols, while sacrificing a limited increase in latency.

Unified Composite Distribution With Applications to Double Shadowed $\kappa$-$\mu$ Fading Channels

In this paper, a mixture Gamma shadowed (MGS) model is proposed as a unified composite distribution via representing the shadowing impact by an inverse Nakagami- <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$m$</tex-math></inline-formula> . The exact expression and the asymptotic behaviour at high average signal-to-noise ratio (SNR) regime of the fundamental statistics of a MGS distribution are derived first. These statistics are then applied to analyze the performance of the wireless communication systems over double shadowed <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$\kappa$</tex-math></inline-formula> - <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$\mu$</tex-math></inline-formula> fading channels. In particular, the outage probability (OP), average bit error probability (ABEP), average channel capacity (ACC), effective capacity (EC) and average area under the receiver operating characteristics curve (AUC) of energy detection (ED) are provided. The numerical and simulation results as well as a comparison with previous exact works are presented to verify the validation of our analysis.

Effective capacity analysis of SIMO system with MRC and SC over Inverse-Gamma shadowing

ABSTRACT Multiple antennas are usually employed to improve the performance of the wireless communication system. To this context, we derive the effective capacity (EC) expressions for Inverse Gamma (I-Gamma) shadowed fading channel, employing maximal ratio combining (MRC) and selection combining (SC) diversity schemes at the receiver (Rx) side. The channels are assumed to be independent and identical distributed (i.i.d.). In addition to this, we also propose the simplified high-power approximation that enables direct interpretation of the system performance concerning system fading parameters. Furthermore, to diminish the effect of shadowing over composite statistics, macroscopic diversity analysis is presented as an application, where Weibull, and I-Gamma models are used to obtain composite statistics. At last, we validate our proposed formulations through the Monte-Carlo simulation.

The effects of university–industry collaboration in preclinical research on pharmaceutical firms’ R&amp;D performance: Absorptive capacity’s role

AbstractPharmaceutical firms frequently engage in preclinical research collaboration with universities. Many of these collaborative preclinical research projects are conducted by firms’ subsidiaries. In this setting, the challenge of transferring knowledge from university–industry collaborations (UICs) to internal research and development (R&amp;D) increases, since knowledge has to be transferred twice: to the subsidiary and to the parent. To benefit from tacit and complex knowledge obtained through collaboration with academic partners, firms need to have a high absorptive capacity. However, existing research on absorptive capacity's effect on the efficacy of UIC has provided mixed results, and the knowledge transfer mechanisms remain unclear, particularly in the case of basic (or preclinical) research and of the complex knowledge transfer process from subsidiaries’ collaborative efforts. Building on the knowledge‐based view and following a multidimensional perspective of absorptive capacity, this study investigates the role a firm's capabilities play in successful university knowledge integration in a firm's internal R&amp;D. Therefore, this paper analyzes both parent firms’ UICs and their subsidiaries’ UICs in basic (preclinical) research. The results of our longitudinal analysis of a unique panel data set of 56 global pharmaceutical firms indicate that firms do successfully exploit valuable knowledge from preclinical research UIC in internal R&amp;D, measured by the number of performed clinical trials. This holds true for the UIC involving the parent firm and its subsidiaries. As transformative learning dimensions of absorptive capacity, high diversity in therapeutic activity and high R&amp;D intensity levels strengthen the positive relationship between parents’ UIC and R&amp;D performance. A high exploration intensity level of the firm and high diversity in therapeutic activity help to transfer the knowledge from subsidiaries’ preclinical research UIC to parents’ innovation projects.