Robust admission control for streaming and elastic services in cellular networks

Abstract-The specific features of cellular networks and especially terminal mobility make the session admission control (SAC) in such networks more complex. This paper studies the robustness of the Virtual Partitioning (VP) admission policy in connection with multiservice cellular networks and considering streaming and elastic traffic in scenarios that must support high overloads. The VP policy is compared with the Multiple Fractional Guard Channel (MFGC) policy. The main contributions of the paper are the study of a new design method, the integration of streaming and elastic traffic, the study of the sensitivity to the channel holding time distribution and the use of absorbing Markov processes to calculate the probability that a handover occurs

Resource management for macrocell users in hybrid access femtocells

Abstract-The constant evolution of mobile-phone traffic demands for novel networking solutions especially focused on indoor environment. In this context, the use of femtocells, i.e., cells with very limited coverage area, has been proposed. In this paper, a femtocell network with hybrid access control mode is considered. The activity profile of the Femtocell Users (FUs) is modeled to compute the maximum achievable throughput and the consumed energy per successfully transmitted data bit by the Macrocell Users (MUs), depending on which set of channels are operated in open access mode, i.e., which channels can be used by MUs. Thus, it is identified how many and which channels must be operated in open access mode, depending on the physical capacities of the channels and the amount of time these channels are not occupied by FUs. The results motivate the need for novel resource management schemes which can dynamically adapt the set of open access channels to the network conditions

Network-coded cooperation and multi-connectivity for massive content delivery

[EN] Massive content delivery is in the spotlight of the research community as both data traffic and the number of connected mobile devices are increasing at an incredibly fast pace. The enhanced mobile broadband (eMBB) is one of the main use cases for the fifth generation of mobile networks (5G), which focuses on transmitting greater amounts of data at higher data rates than in the previous generations, but also on increasing the area capacity (given in bits per second per square meter) and reliability. However, the broadcast and multicast implementation in 5G and presents several drawbacks such as unexpected disconnections and the lack of device-specific QoS guarantees. As a result, whenever the exact same content is to be delivered to numerous mobile devices simultaneously, this content must be replicated. Hence, the same number of parallel unicast sessions as users are needed. Therefore, novel systems that provide efficient massive content delivery and reduced energy consumption are needed. In this paper, we present a network-coded cooperation (NCC) protocol for efficient massive content delivery and the analytical model that describes its behavior. The NCC protocol combines the benefits of cooperative architectures known as mobile clouds (MCs) with Random Linear Network Coding (RLNC). Our results show the benefits of our NCC protocol when compared to the establishment of numerous parallel unicast sessions are threefold: offload data traffic from the cellular link, reduce the energy consumption at the cooperating users, and provide throughput gains when the cellular bandwidth is insufficient.This work was supported in part by the European Union's H2020 Research and Innovation Program under Grant H2020-MCSA-ITN-2016-SECRET 722424. The work of Vicent Pla and Jorge Martinez-Bauset was supported under Grant PGC2018-094151-B-I00 and Grant RED2018-102585-T (MCIU/AEI/FEDER,UE)Leyva-Mayorga, I.; Torre, R.; Pla, V.; Pandi, S.; Nguyen, GT.; Martínez Bauset, J.; Fitzek, FHP. (2020). Network-coded cooperation and multi-connectivity for massive content delivery. IEEE Access. 8:15656-15672. https://doi.org/10.1109/ACCESS.2020.29672781565615672

Optimal Radio Access Technology Selection on Heterogeneous Networks

[EN] The joint management of radio resources in heterogeneous networks is considered to improve their capacity. We propose joint schemes for admission control and access technology selection with vertical handoffs. Optimal policies are found for wireless networks that support two access techniques and cover the same geographical area. In addition, the system under study also supports heterogeneous traffic of two types: streaming and elastic. We explore the optimization of different functions expressed in terms of blocking probabilities and throughput. An exhaustive numerical analysis allows us to characterize the optimal admission policies according to the arrival type and system state. Based on this characterization, heuristic policies are designed and their performance is compared to the one obtained by previously proposed schemes. This analysis is also done when constraints, expressed in terms of blocking probability bounds, are added. An extension of the previous system that includes vertical handoffs, in order to evaluate their impact on the system performance, is also studied. For the four types of vertical handoffs considered, we determine and characterize the optimal policies according to the arrival type, system state and vertical handoff action. Since it is not computationally feasible to calculate the optimal policies online, new heuristic policies with vertical handoffs are design and evaluated. It is found that the heuristic policies scale with the system size without requiring any adjustment, their performance is very close to the one obtained by the optimal policies and they are simple to implement, and, therefore, can be used online. In addition, we find that the heuristic policies are insensitive to the service time of the voice sessions and the elastic flow sizes beyond the mean. Finally, in order to take into account the cost of performing vertical handoffs, a new optimization problem is formulated that relates the costs of voice and data blocking with the costs of vertical handoffs.This work was supported by the Spanish Government and the European Commission through projects TIN2010- 21378-C02-02 and TIN2008-06739-C04-02.Pacheco Páramo, DF.; Pla, V.; Casares Giner, V.; Martínez Bauset, J. (2012). Optimal Radio Access Technology Selection on Heterogeneous Networks. Physical Communication. 5(3):253-271. https://doi.org/10.1016/j.phycom.2012.02.009S2532715

Dynamic Spectrum Sharing in Cognitive Radio Networks Using Truthful Mechanisms and Virtual Currency

In cognitive radio networks, there are scenarios where secondary users (SUs) utilize opportunistically the spectrum originally allocated to primary users (PUs). The spectrum resources available to SUs fluctuates over time due to PUs activity, SUs mobility and competition between SUs. In order to utilize these resources efficiently spectrum sharing techniques need to be implemented. In this paper we present an approach based on game-theoretical mechanism design for dynamic spectrum sharing. Each time a channel is not been used by any PU, it is allocated to SUs by a central spectrum manager based on the valuations of the channel reported by all SUs willing to use it. When an SU detects a free channel, it estimates its capacity according to local information and sends the valuation of it to the spectrum manager. The manager calculates a conflict-free allocation by implementing a truthful mechanism. The SUs have to pay for the allocation an amount which depends on the set of valuations. The objective is not to trade with the spectrum, but to share it according to certain criteria. For this, a virtual currency is defined and therefore monetary payments are not necessary. The spectrum manager records the credit of each SU and redistributes the payments to them after each spectrum allocation. The mechanism restricts the chances of each SU to be granted the channel depending on its credit availability. This credit restriction provides an incentive to SUs to behave as benefit maximizers. If the mechanism is truthful, their best strategy is to communicate the true valuation of the channel to the manager, what makes possible to implement the desired spectrum sharing criteria. We propose and evaluate an implementation of this idea by using two simple mechanisms which are proved to be truthful, and that are tractable and approximately efficient. We show the flexibility of these approach by illustrating how these mechanisms can be modified to achieve different sharing objectives which are trade-offs between efficiency and fairness. We also investigate how the credit restriction and redistribution affects the truthfulness of these mechanisms.This work was supported by the Spanish government through Projects TIN 2008-06739-C04-02 and TIN 2010-21378-C02-02.Vidal Catalá, JR.; Pla, V.; Guijarro Coloma, LA.; Martínez Bauset, J. (2013). Dynamic Spectrum Sharing in Cognitive Radio Networks Using Truthful Mechanisms and Virtual Currency. Ad Hoc Networks. 11:1858-1873. https://doi.org/10.1016/j.adhoc.2013.04.010S185818731

Modelling the time-varying cell capacity in LTE networks

In wireless orthogonal frequency-division multiple access (OFDMA) based networks like Long Term Evolution (LTE) or Worldwide Interoperability for Microwave Access (WiMAX) a technique called adaptive modulation and coding (AMC) is applied. With AMC, different modulation and coding schemes (MCSs) are used to serve different users in order to maximise the throughput and range. The used MCS depends on the quality of the radio link between the base station and the user. Data is sent towards users with a good radio link with a high MCS in order to utilise the radio resources more efficiently while a low MCS is used for users with a bad radio link. Using AMC however has an impact on the cell capacity as the quality of a radio link varies when users move around; this can even lead to situations where the cell capacity drops to a point where there are too little radio resources to serve all users. AMC and the resulting varying cell capacity notably has an influence on admission control (AC). AC is the algorithm that decides whether new sessions are allowed to a cell or not and bases its decisions on, amongst others, the cell capacity. The analytical model that is developed in this paper models a cell with varying capacity caused by user mobility using a continuous -time Markov chain (CTMC). The cell is divided into multiple zones, each corresponding to the area in which data is sent towards users using a certain MCS and transitions of users between these zones are considered. The accuracy of the analytical model is verified by comparing the results obtained with it to results obtained from simulations that model the user mobility more realistically. This comparison shows that the analytical model models the varying cell capacity very accurately; only under extreme conditions differences between the results are noticed. The developed analytical and simulation models are then used to investigate the effects of a varying cell capacity on AC. Also, an optimisation algorithm that adapts the parameter of the AC algorithm which determines the amount of resources that are reserved in order to mitigate the effects of the varying cell capacity is studied using the models. Updating the parameter of the AC algorithm is done by reacting to certain triggers that indicate good or bad performance and adapt the parameters of the AC algorithm accordingly. Results show that using this optimisation algorithm improves the quality of service (QoS) that is experienced by the users.This work was partially supported by the Spanish Government through project TIN2010-21378-C02-02 and contract BES-2007-15030.Sas, B.; Bernal Mor, E.; Spaey, K.; Pla, V.; Blondia, C.; Martínez Bauset, J. (2014). Modelling the time-varying cell capacity in LTE networks. Telecommunication Systems. 55(2):299-313. https://doi.org/10.1007/s11235-013-9782-2S2993135523GPP (2010). 3GPP TR 36.213: Evolved Universal Terrestrial Radio Access (E-UTRA); Radio Resource Control (RRC); Physical layer procedures, June 2010.3GPP (2010). 3GPP TR 36.942: Evolved Universal Terrestrial Radio Access (E-UTRA); Radio Resource Control (RRC); Radio Frequency (RF) system scenarios, September 2010.Al-Rawi, M., & Jäntti, R. (2009). Call admission control with active link protection for opportunistic wireless networks. Telecommunications Systems, 41(1), 13–23.Bhatnagar, S., & Reddy, B.B.I. (2005). Optimal threshold policies for admission control in communication networks via discrete parameter stochastic approximation. Telecommunications Systems, 29(1), 9–31.Camp, T., Boleng, J., & Davies, V. (2002). A survey of mobility models for ad hoc network research. Wireless Communications and Mobile Computing, 2(5), 483–502.E3. ict-e3.eu.Elayoubi, S.-E., & Chahed, T. (2005). Admission control in the downlink of WCDMA/UMTS. In LNCS: Vol. 3427. Mobile and wireless systems (pp. 136–151).Garcia, D., Martinez, J., & Pla, V. (2005). Admission control policies in multiservice cellular networks: optimum configuration and sensitivity. In G. Kotsis, & O. Spaniol (Eds.), Lecture notes in computer science: Vol. 3427. Wireless systems and mobility in next generation Internet (pp. 121–135).Guo, J., Liu, F., & Zhu, Z. (2007). Estimate the call duration distribution parameters in GSM system based on K-L divergence method. In International conference on wireless communications, networking and mobile computing (pp. 2988–2991), Shanghai, China, September 2007.Hossain, M., Hassan, M., & Sirisena, H. R. (2004). Adaptive resource management in mobile wireless networks using feedback control theory. Telecommunications Systems, 24(3–4), 401–415.Jeong, S.S., Han, J.A., & Jeon, W.S. (2005). Adaptive connection admission control scheme for high data rate mobile networks. In IEEE 62nd Vehicular technology conference, 2005. VTC-2005-Fall (Vol. 4, pp. 2607–2611).Kim, D.K., Griffith, D., & Golmie, N. (2010). A novel ring-based performance analysis for call admission control in wireless networks. IEEE Communications Letters, 14(4), 324–326.Latouche, G., & Ramaswami, V. (1999). Introduction to matrix analytic methods in stochastic modeling. ASA-SIAM. Baltimore: Philadelphia.MONOTAS. http://www.macltd.com/monotas .Neuts, M. (1981). Matrix-geometric solutions in stochastic models: an algorithmic approach. Baltimore: The Johns Hopkins University Press.NGMN. NGMN Radio Access Performance Evaluation Methodology, January 2008.NGMN. www.ngmn.org .Prehofer, C., & Bettstetter, C. (2005). Self-organization in communication networks: principles and design paradigms. IEEE Communications Magazine, 43(7), 78–85.Ramjee, R., Nagarajan, R., & Towsley, D. (1997). On optimal call admission control in cellular networks. Wireless Networks, 3(1), 29–41.Siwko, J., & Rubin, I. (2001). Call admission control for capacity-varying networks. Telecommunications Systems, 16(1–2), 15–40.SOCRATES. www.fp7-socrates.eu .Spaey, K., Sas, B., & Blondia, C. (2010). Self-optimising call admission control for LTE downlink. In COST 2100 TD(10)10056, Joint Workshop COST 2100 SWG 3.1 & FP7-ICT-SOCRATES, Athens, Greece.Spilling, A. G., Nix, A. R., Beach, M. A., & Harrold, T. J. (2000). Self-organisation in future mobile communications. Electronics & Communication Engineering Journal, 3, 133

Deep Reinforcement Learning Mechanism for Dynamic Access Control in Wireless Networks Handling mMTC

[EN] One important issue that needs to be addressed in order to provide effective massive deployments of IoT devices is access control. In 5G cellular networks, the Access Class Barring (ACB) method aims at increasing the total successful access probability by delaying randomly access requests. This mechanism can be controlled through the barring rate, which can be easily adapted in networks where Human-to-Human (H2H) communications are prevalent. However, in scenarios with massive deployments such as those found in IoT applications, it is not evident how this parameter should be set, and how it should adapt to dynamic traffic conditions. We propose a double deep reinforcement learning mechanism to adapt the barring rate of ACB under dynamic conditions. The algorithm is trained with simultaneous H2H and Machine-to-Machine (M2M) traffic, but we perform a separate performance evaluation for each type of traffic. The results show that our proposed mechanism is able to reach a successful access rate of 100 % for both H2H and M2M UEs and reduce the mean number of preamble transmissions while slightly affecting the mean access delay, even for scenarios with very high load. Also, its performance remains stable under the variation of different parameters. (C) 2019 Elsevier B.V. All rights reserved.The research of D. Pacheco-Paramo was supported by Universidad Sergio Arboleda, P.t. Tecnologias para la inclusion social y la competitividad economica. 0.E.6. The research of L Tello-Oquendo was conducted under project CONV.2018-ING010. Universidad Nacional de Chimborazo. The research of V. Pla and J. Martinez-Bauset was supported by Grant PGC2018-094151-B-I00 (MCIU/AEI/FEDER,UE).Pacheco-Paramo, DF.; Tello-Oquendo, L.; Pla, V.; Martínez Bauset, J. (2019). Deep Reinforcement Learning Mechanism for Dynamic Access Control in Wireless Networks Handling mMTC. Ad Hoc Networks. 94:1-14. https://doi.org/10.1016/j.adhoc.2019.101939S1149

Robustness of optimal channel reservation using handover prediction in multiservice wireless networks

The aim of our study is to obtain theoretical limits for the gain that can be expected when using handover prediction and to determine the sensitivity of the system performance against different parameters. We apply an average-reward reinforcement learning approach based on afterstates to the design of optimal admission control policies in mobile multimedia cellular networks where predictive information related to the occurrence of future handovers is available. We consider a type of predictor that labels active mobile terminals in the cell neighborhood a fixed amount of time before handovers are predicted to occur, which we call the anticipation time. The admission controller exploits this information to reserve resources efficiently. We show that there exists an optimum value for the anticipation time at which the highest performance gain is obtained. Although the optimum anticipation time depends on system parameters, we find that its value changes very little when the system parameters vary within a reasonable range. We also find that, in terms of system performance, deploying prediction is always advantageous when compared to a system without prediction, even when the system parameters are estimated with poor precision. © Springer Science+Business Media, LLC 2012.The authors would like to thank the reviewers for their valuable comments that helped to improve the quality of the paper. This work has been supported by the Spanish Ministry of Education and Science and European Comission (30% PGE, 70% FEDER) under projects TIN2008-06739-C04-02 and TIN2010-21378-C02-02 and by Comunidad de Madrid through project S-2009/TIC-1468.Martínez Bauset, J.; Giménez Guzmán, JM.; Pla, V. (2012). Robustness of optimal channel reservation using handover prediction in multiservice wireless networks. 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Joint Optimization of Detection Threshold and Resource Allocation in Infrastructure-based Multi-band Cognitive Radio Networks

[EN] Consider an infrastructure-based multi-band cognitive radio network (CRN) where secondary users (SUs) opportunistically access a set of sub-carriers when sensed as idle. The carrier sensing threshold which affects the access opportunities of SUs is conventionally regarded as static and treated independently from the resource allocation in the model. In this article, we study jointly the optimization of detection threshold and resource allocation with the goal of maximizing the total downlink capacity of SUs in such CRNs. The optimization problem is formulated considering three sets of variables, i.e., detection threshold, sub-carrier assignment and power allocation, with constraints on the PUs¿ rate loss and the power budget of the CR base station. Two schemes, referred to as offline and online algorithms respectively, are proposed to solve the optimization problem. While the offline algorithm finds the global optimal solution with high complexity, the online algorithm provides a close-to-optimal solution with much lower complexity and realtime capability. The performance of the proposed schemes is evaluated by extensive simulations and compared with the conventional static threshold selection algorithm specified in the IEEE 802.22 standard.This work is supported by the EU FP7 S2EuNet project (247083), the National Nature Science Foundation of China (NSF61121001), Program for New Century Excellent Talents in University (NCET) and the Spanish Ministry of Education and Science under project (TIN2008-06739-C04-02).Shi, C.; Wang, Y.; Wang, T.; Zhang, P.; Martínez Bauset, J.; Li, FY. (2012). Joint Optimization of Detection Threshold and Resource Allocation in Infrastructure-based Multi-band Cognitive Radio Networks. 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Technol 2011, 60(4):1699-1713.Kang X, Liang Y, Nallanathan A, Garg H, Zhang R: Optimal power allocation for fading channels in cognitive radio networks: ergodic capacity and outage capacity. IEEE Trans. Wirel. Commun 2009, 8(2):940-950.Bansal G, Hossain M, Bhargava V: Optimal and suboptimal power allocation schemes for OFDM-based cognitive radio systems. IEEE Trans. Wirel. Commun 2008, 7(11):4710-4718.Yucek T, Arslan H: A survey of spectrum sensing algorithms for cognitive radio applications. IEEE Commun. Surv. Tutor 2009, 11: 116-130.Cordeiro C, Ghosh M, Cavalcanti D, Challapali K: Spectrum sensing for dynamic spectrum access of TV bands. In Proceedings of the 2nd Cognitive Radio Oriented Wireless Networks and Communications (CrownCom’07). (Orlando, FL, USA, 1–3 Aug 2007);Chong J, Sung D, Sung Y: Cross-layer performance analysis for CSMA/CA protocols: impact of imperfect sensing. IEEE Trans. Veh. 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Mortality and pulmonary complications in patients undergoing surgery with perioperative SARS-CoV-2 infection: an international cohort study

Background: The impact of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) on postoperative recovery needs to be understood to inform clinical decision making during and after the COVID-19 pandemic. This study reports 30-day mortality and pulmonary complication rates in patients with perioperative SARS-CoV-2 infection. Methods: This international, multicentre, cohort study at 235 hospitals in 24 countries included all patients undergoing surgery who had SARS-CoV-2 infection confirmed within 7 days before or 30 days after surgery. The primary outcome measure was 30-day postoperative mortality and was assessed in all enrolled patients. The main secondary outcome measure was pulmonary complications, defined as pneumonia, acute respiratory distress syndrome, or unexpected postoperative ventilation. Findings: This analysis includes 1128 patients who had surgery between Jan 1 and March 31, 2020, of whom 835 (74·0%) had emergency surgery and 280 (24·8%) had elective surgery. SARS-CoV-2 infection was confirmed preoperatively in 294 (26·1%) patients. 30-day mortality was 23·8% (268 of 1128). Pulmonary complications occurred in 577 (51·2%) of 1128 patients; 30-day mortality in these patients was 38·0% (219 of 577), accounting for 81·7% (219 of 268) of all deaths. In adjusted analyses, 30-day mortality was associated with male sex (odds ratio 1·75 [95% CI 1·28–2·40], p\textless0·0001), age 70 years or older versus younger than 70 years (2·30 [1·65–3·22], p\textless0·0001), American Society of Anesthesiologists grades 3–5 versus grades 1–2 (2·35 [1·57–3·53], p\textless0·0001), malignant versus benign or obstetric diagnosis (1·55 [1·01–2·39], p=0·046), emergency versus elective surgery (1·67 [1·06–2·63], p=0·026), and major versus minor surgery (1·52 [1·01–2·31], p=0·047). Interpretation: Postoperative pulmonary complications occur in half of patients with perioperative SARS-CoV-2 infection and are associated with high mortality. Thresholds for surgery during the COVID-19 pandemic should be higher than during normal practice, particularly in men aged 70 years and older. Consideration should be given for postponing non-urgent procedures and promoting non-operative treatment to delay or avoid the need for surgery. Funding: National Institute for Health Research (NIHR), Association of Coloproctology of Great Britain and Ireland, Bowel and Cancer Research, Bowel Disease Research Foundation, Association of Upper Gastrointestinal Surgeons, British Association of Surgical Oncology, British Gynaecological Cancer Society, European Society of Coloproctology, NIHR Academy, Sarcoma UK, Vascular Society for Great Britain and Ireland, and Yorkshire Cancer Research