Number Of UEs Research Articles

Adaptive User Pairing in Multi-IRS-Aided Massive MIMO-NOMA Networks: Spectral Efficiency Maximization and Deep Learning Design

In this paper, we propose an adaptive user pairing (AUP) scheme in multi-intelligent reflecting surface (IRS)-aided massive multiple-input multiple-output (MIMO)-non-orthogonal multiple access (NOMA) networks. In the AUP scheme, two users with different channel conditions are selected for user pairing while multiple IRSs assist to improve received signal quality at users. We consider the problem of jointly optimizing the precoding matrix, the phase shift of IRSs, and the user pairing element to maximize the overall spectral efficiency (SE) subject to the maximum power budget at the base station (BS) and user-specific quality-of-service (QoS). The SE problem formulated as the maximization of non-concave functions involves a mixed-integer program, which is very challenging to solve optimally. To tackle this problem, we first relax the user pairing elements to be continuous and then transform the formulated problem into an equivalent non-convex problem with a more tractable form. We then apply the iterative algorithm (IA) with low complexity to guarantee convergence at a relative optimum. Towards real-time optimization, we propose a deep learning (DL) framework to predict the optimal solution of the precoding matrix, the phase shift of IRSs, and user pairing elements according to the user’s locations and channel gains. Compared to the conventional optimization method, the DL-based optimization framework can achieve the optimal solution within a very short time via an efficient inference process. Numerical results verify that the proposed algorithm improves the SE over state-of-the-art approaches. Moreover, the effects of essential parameters such as the total BS transmit power, the number of UEs, IRSs, and BS’s antennas on the system are discussed and evaluated to show the effectiveness of the proposed scheme in balancing resource utilization.

Improving spectral efficiency via pilot assignment and subarray selection under realistic XL-MIMO channels

The main requirements for 5G and beyond connectivity include a uniform high quality of service, which can be attained in crowded scenarios by extra-large MIMO (XL-MIMO) systems. Another requirement is to support an increasing number of connected users in (over)crowded machine-type communication (mMTC). In such scenarios, pilot assignment (PA) becomes paramount to reduce pilot contamination and consequently improve spectral efficiency (SE). We propose a novel quasi-optimal low-complexity iterative pilot assignment strategy for XL-MIMO systems, based on a genetic algorithm (GA). The proposed GA-based PA procedure turns the quality of service more uniform, taking into account the normalized mean-square error (NMSE) of channel estimation from each candidate of the population. The simulations reveal that the proposed iterative procedure minimizes the channel estimation NMSE averaged over the UEs. The second procedure is the subarray (SA) selection. In XL-MIMO systems, commonly a UE is close to an SA antenna subset such that a sufficient data rate can be achieved if only a specific SA serves that UE. Thus, an SA selection procedure is investigated to make the system scalable by defining the maximum number of UEs each SA can help. Hence, the SA clusters are formatted based on the PA decision. Furthermore, we introduce an appropriate channel model for XL-MIMO, which considers a deterministic LoS component with a distance-dependent probability of existence combined with a stochastic spatially correlated Rayleigh NLoS fading component. The developed simulations and analyses rely on this suitable channel model under realistic assumptions of pilot contamination and correlated channels.

The effects of intravenous remifentanil on umbilical artery serum-derived exosomes in parturients undergoing epidural anesthesia: a randomized trial

BackgroundUmbilical artery serum-derived exosomes (UEs) serve as messengers for maternal–fetal information exchange and cellular regulation. Intravenous remifentanil could be considered as an effective adjunct to epidural anesthesia in providing a favorable analgesia effect for cesarean section (C-section), but its effects on UEs are currently unknown.MethodsFrom 01/12/2021 to 30/06/2022, eligible parturients scheduled for repeated C-section at the First Affiliated Hospital of Wenzhou Medical University were randomized to receive either an intravenous bolus (0.15 μg/kg) followed by a continuous infusion (0.075 μg/kg/min) of remifentanil or normal saline throughout the procedure. The primary outcome was the number of UEs. Secondary outcomes included the size and protein amount of UEs, the vital signs, visceral pain score, sedation score, maternal satisfaction score, Apgar score, the incidence of neonatal asphyxia, umbilical arterial pH, and the presence of complications.ResultsNanoparticle tracking analysis indicated similar size of UEs between the two groups, but the number and protein amount of UEs were increased in the remifentanil group compared to the control group (P < 0.05). In parturients receiving remifentanil, visceral pain scores were decreased, which was accompanied by the increased scores of maternal satisfaction with the anesthetic method (P < 0.05). Other maternal and neonatal outcomes were comparable between the two groups (P > 0.05).ConclusionThe intravenous administration of remifentanil increased the number of UEs in parturients undergoing repeated C-section under epidural anesthesia, with improved birth experience and minimal neonatal complications.

Energy-Efficient Sleep Mode Schemes for Cell-Less RAN in 5G and Beyond 5G Networks

In 5G and beyond 5G networks, the new cell-less radio access network architecture is adopted to overcome the extreme network capacity challenges generated by massive wireless devices used for diverse scenarios and various applications. At the same time, the evolution of mobile communications faces the important challenge of increased network power consumption. To fulfill user demands for various user densities and meanwhile reduce the power consumption, we present a novel energy-efficiency enhancement scheme, i.e., <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$(3\times E)$ </tex-math></inline-formula> to increase the transmission rate per energy unit, with stable performance within the cell-less radio access network (RAN) architecture. Our proposed <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$(3\times E)$ </tex-math></inline-formula> scheme activates two-step sleep modes (i.e., certain phase and conditional phase) through the intelligent interference management for temporarily switching access points (APs) to sleep, optimizing the network energy efficiency (EE) in highly loaded scenarios, as well as in scenarios with lower load. An intelligent control over underutilized/unused APs is considered, taking their interference contribution into account as the primary main criteria in addition to load-based conditional criteria. Therefore, our proposed scheme assures a stable performance enhancement and maintains an efficient power saving when the number of UEs increases, improving existing works not addressing this performance stability in peak-traffic hours. Simulation results show that the network EE is improved up to 30% compared to the reference algorithm and up to 60% with respect to the baseline algorithm in which all APs are active all the time.

Reducing Pediatric Unplanned Extubation Across Multiple ICUs Using Quality Improvement.

Unplanned extubation (UE) in pediatric patients can result in significant harm or mortality. In our institution, efforts to reduce UE in the ICU were siloed and learnings were not shared. Our goal was to implement shared initiatives across ICUs in a pediatric institution using quality improvement methodology, with the global aim of reducing serious harm caused by UEs. The study was conducted as a single-center prospective quality improvement initiative in the pediatric, neonatal, and cardiac ICUs of a large, freestanding academic pediatric hospital. Using the model for improvement and plan-do-study-act cycles, our multidisciplinary team implemented multiple interventions to reduce UEs. The primary measure monitored was the monthly UE rate, defined as the number of UEs per 100 ventilator days, which was tracked over time using statistical control charts. The overall monthly institutional UE rate was reduced from 1.22 UE per 100 ventilator days to 0.2 UE per 100 ventilator days, representing an 84% improvement in rate and reduction of harm. Sixteen percent to 21% of UEs required additional resources because of a difficult airway, and 10% to 22% of UEs resulted in cardiovascular collapse requiring resuscitation. Significant harm is associated with UEs in pediatric patients. We implemented a bundle for UE reduction across all ICU populations in a pediatric hospital and significantly reduced the rate of UE within our institution and within each individual unit. Allowing variation for implementation of interventions by unit, although targeting a common goal, contributed to overall success and sustainability.

Sensing-Based Grant-Free Scheduling for Ultra Reliable Low Latency and Deterministic Beyond 5G Networks

5G and beyond networks should efficiently support services with stringent and diverse QoS requirements. This includes services for verticals that demand Ultra Reliable and Low Latency Communications (URLLC). Scheduling strongly impacts the communication latency, and 5G NR introduces grant-free scheduling to reduce the latency at the radio level. Grant-free scheduling can use shared resources and the transmission of <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">K</i> replicas per packet to increase the packet delivery ratio and efficiently utilize the spectrum. Previous studies have shown that existing 5G NR grant-free scheduling has limitations to sustain URLLC requirements for aperiodic (or uncertain) and deterministic traffic that is characteristic of verticals such as Industry 4.0 or manufacturing. In this context, this paper proposes and evaluates a novel grant-free scheduling scheme that can efficiently support deterministic and aperiodic uplink traffic. The scheme avoids packet collisions among UEs sharing resources using a priority-based contention resolution process that relies on the transmission of announcement messages in minislots and a local channel sensing process. This study demonstrates that the proposed sensing-based grant-free scheduling scheme outperforms current 5G NR grant-free scheduling implementations, and can support a higher number of UEs with URLLC and deterministic requirements with a considerably lower number of radio resources.

The Adaptive Random Access Carrier Allocation Scheme in NB-IoT Networks

The rapid progress of the deployment of IoT services pushes the evolution of wireless communication techniques. Because the number of IoT devices is much more than that of the human-held devices for traditional services. It introduces the random access issue in radio networks. In order to support massive IoT devices to transmit data in NB-IoT, the release 14 of 3 GPP provides the preambles in non-anchor carrier for random access. However, if more non-anchor carriers are provided for random access, the resource of uplink shared channel will be compressed. The use of non-anchor carrier for random access preambles shall be carefully allocated for effective resource utilization. In this paper, we propose the adaptive non-anchor allocation algorithm by referring to the collision report flag (CRF) from the user equipment. The proposed CRF algorithm considers the congestion status of uplink to adjust the number of non-anchor carriers in flexible way for better random access experience of huge random access attempts condition. The simulation results show that the proposed algorithm achieves high success access ratio and effective non-anchor carrier utilization when comparing to that of the fixed allocation schemes. The proposed scheme can save 5 - 10 numbers of non-anchor carriers for the number of UEs varies from 15,000 to 37,500 when comparing to the fixed 15 non-anchor carriers scheme under the similar successful access ratio.

COVID-EX. Influence of the COVID-19 pandemic on the rate of unplanned extubations (UE) in intensive care units (ICUs): A case-control study

In ICUs, many patients are intubated. UE is an indicator of the quality of care.Isolation associated with "air" precautions may increase the number of UEs in mechanically ventilated (MV) COVID patients.The main aim of the study was to compare the rate of UE between a COVID-19 period and a control period. The secondary aims were to identify UE risk factors and to study the experience of caregivers during the COVID-19 period. The method of choice was a retrospective single center case-control study. MV patients aged ≥ 18 years were eligible in two periods: the control period from 01/02/2020 to 29/02/2020, and the COVID-19 period from 01/03/2020 to 31/03/2020. An anonymous survey was given to ICU caregivers in Vannes Hospital. The UE rate was 17% (n=7) vs. 20% (n=9) control period vs. COVID-19 period (p=0.58), with nocturnal preponderance (75%). A quarter (n=4) of patients fulfill MV weaning criteria at the time of UE. A 71% (n=49) survey response rate was obtained. The COVID-19 period had a higher estimated UE risk for 76% (n=37) of caregivers, who felt that they had a greater workload, difficulties with monitoring, and decreased regular visits to patients' rooms. Contrary to the caregiver experience, we reported a similar UE rate over both the COVID-19 period and the control period.

Achieving Near Optimal Sum Rate in Downlink Massive Multiple Antenna System

In this paper, a massive multiple input multiple output (massive-MIMO) system with up to 600 base station antennas exploiting the channel state information (CSI) to improve the capacity of system while serving multiple UEs was proposed. Two precoding schemes: zero-forcing (ZF) and maximum ratio transmission (MRT) were implemented and used to test the effectiveness of the proposed system. In order to study the effectiveness of the system, its performance was analyzed in terms of achievable sum rate. MATLAB codes were developed for the simulations test conducted to study the sum rate performance of the system. Simulations were carried out by varying the number of base station antennas from 300 to 600 with respect to the number of users to determine the achievable sum rate of the system. Results showed that increasing the number of base station antennas brings about better spectral efficiency for optimal multiuser interference reduction such that highest sum rates: 317.5 Bits/s/Hz and 317.0 Bits/s/Hz, were achieved using ZF considering vector/matrix normalizations for number of base station antennas (M) equal to 600 and number of UEs (K) equal to 200 when sum rate is plotted against number of base station antennas in high transmitted power scenarios. Also, when sum rate is plotted against number of users, the system achieves highest sum rate of 433.7 Bits/s/Hz and 433.3 Bits/s/Hz for ZF considering vector/matrix normalizations at M 600, for K equal to 200 for high transmitted power scenarios. The results show that for low transmitted power, MRT outperforms ZF, while ZF gives better performance than MRT for high transmitted power. Generally, the results obtained revealedthat increasing the number of base station antennas can provide near optimal (or best possible) achievable sum rate and mitigate multiuser interference (MUI).

Deep Grid Scheduler for 5G NB-IoT Uplink Transmission

Since the birth of narrowband Internet of Things (NB-IoT), the Internet of Things (IoT) industry has made a considerable progress in the application for smart cities, smart manufacturing, and healthcare. Therefore, the number of UEs is increasing exponentially, which brings considerable pressure to the efficient resource allocation for the bandwidth and power constrained NB-IoT networks. In view of the conventional algorithms that cannot dynamically adjust resource allocation, resulting in a low resource utilization and prone to resource fragmentation, this paper proposes a double deep Q-network (DDQN)-based NB-IoT dynamic resource allocation algorithm. It first builds an NB-IoT environment model based on the real environment. Then, the DDQN algorithm interacts with the NB-IoT environment model to learn and optimize resource allocation strategies until it converges to the optimum. Finally, the simulation results show that the DDQN-based NB-IoT dynamic resource allocation algorithm is better than the traditional algorithm in the resource utilization, average transmission rate, and UE average queuing time.

Applications of Extreme Gradient Boosting for Intelligent Handovers from 4G To 5G (mm Waves) Technology with Partial Radio Contact

In a network topology, where 5G (mm Waves) have better coverage footprint compared to 4G (LTE or LTE-A) technology, mobile devices would generally be handed over from 4G to 5G. In this work, a supervised intelligent prediction technique for improved handover success rate (HSR) from 4G to 5G technology is proposed. The technique is applicable for base stations enabled with sub-6-GHz and mm-wave bands. This technique is novel since it can predict HSR even before switching to 5G radio circuitry or initiating its measurement gap for acquisition of mm-wave reference signal received power (RSRP) unlike conventional algorithms. Thus, preempting all handovers which are likely to fail will provide improvements in latency, delay, and handover success rate, as well as decrease call drops. Therefore, this research work answers previous research shortcomings and can unleash applications of supervised intelligent algorithms for predicting the HSR from 4G to 5G. The proposed algorithm is validated by showing improvements obtained through simulation results performed using Python-based framework. The proposed algorithm is tested for reliability with increasing parameters such as the intensity number of UEs and simulation time. Improvements in standard handover algorithm are also proposed.

On the Capacity of 5G NR Grant-Free Scheduling with Shared Radio Resources to Support Ultra-Reliable and Low-Latency Communications.

5G and beyond networks are being designed to support the future digital society, where numerous sensors, machinery, vehicles and humans will be connected in the so-called Internet of Things (IoT). The support of time-critical verticals such as Industry 4.0 will be especially challenging, due to the demanding communication requirements of manufacturing applications such as motion control, control-to-control applications and factory automation, which will require the exchange of critical sensing and control information among the factory nodes. To this aim, important changes have been introduced in 5G for Ultra-Reliable and Low-Latency Communications (URLLC). One of these changes is the introduction of grant-free scheduling for uplink transmissions. The objective is to reduce latency by eliminating the need for User Equipments (UEs—sensors, devices or machinery) to request resources and wait until the network grants them. Grant-free scheduling can reserve radio resources for dedicated UEs or for groups of UEs. The latter option is particularly relevant to support applications with aperiodic or sporadic traffic and deterministic low latency requirements. In this case, when a UE has information to transmit, it must contend for the usage of radio resources. This can lead to potential packet collisions between UEs. 5G introduces the possibility of transmitting K replicas of the same packet to combat such collisions. Previous studies have shown that grant-free scheduling with K replicas and shared resources increases the packet delivery. However, relying upon the transmission of K replicas to achieve a target reliability level can result in additional delays, and it is yet unknown whether grant-free scheduling with K replicas and shared resources can guarantee very high reliability levels with very low latency. This is the objective of this study, that identifies the reliability and latency levels that can be achieved by 5G grant-free scheduling with K replicas and shared resources in the presence of aperiodic traffic, and as a function of the number of UEs, reserved radio resources and replicas K. The study demonstrates that current Fifth Generation New Radio (5G NR) grant-free scheduling has limitations to sustain stringent reliability and latency levels for aperiodic traffic.

TOA positioning for uplink cooperative NOMA in 5G networks

Wireless geolocation considering Non-Orthogonal Multiple Access (NOMA) is particular of interest for enabling high precision location based services (LBSs) in 5G networks. In this paper, we study the fundamental limits of Time-of-arrival (TOA) positioning for uplink cooperative NOMA in the power domain under different 5G network conditions with special emphasis on the user fairness. The theoretical analysis is conducted in terms of Cramer–Rao Lower Bound (CRLB) expressions. More specifically, the CRLB of TOA positioning for uplink cooperative NOMA and OMA are obtained considering Amplify-and-Forward (AF) and Decode-and-Forward (DF) relaying strategies. Then, the numerical results of both TOA positioning for uplink cooperative NOMA and OMA are obtained and compared under different 5G network scenarios. In particular, the effects of successive interference cancellation (SIC) error, bandwidth, number of relays, and number of UEs and relaying strategy type on the performance of position accuracy are investigated. The results reveal that the cooperative NOMA outperforms cooperative OMA in terms of location estimation accuracy under different network conditions. Furthermore, the results suggest that TOA positioning of cooperative NOMA is a promising choice for supporting high precision LBSs in 5G networks.

Radio Resource Scheduling for Narrowband Internet of Things Systems: A Performance Study

In the context of the IoT, mMTC technology in 5G enables a range of new applications. The 3GPP NB-IoT introduced in Release 13 is a major enhancement toward mMTC to support devices requiring low data rate, low cost, and long battery life. Previous works suggested that NB-IoT physical channel characteristics have potential to fulfill design requirements. From the system point of view, the interaction among UEs and application data transmission procedures have to be further evaluated considering radio resource scheduling. In this article, we identify radio resource scheduling issues for NB-IoT systems and provide a comprehensive performance evaluation. We consider control plane optimization procedures with a massive number of UEs in mixed CE levels. Using a scheduling architecture verified with derived effective data rates, we show the effects of essential parameters on control channel allocation and data scheduling. Given our scheduling settings in anchor carriers, the number of transmitted data packets achieves about 65,000 per cell per hour with mixed CE levels. The results satisfy the design goal of NB-IoT data transmission in 3GPP TR 45.820.

Power optimization with low complexity using scaled beamforming approach for a massive MIMO and small cell scenario

Present wireless generation is now evolving from 4G to 5G with a large number of clients. Researchers across the globe are working to sustain the quality of service level, while meeting the increasing demand of the clients. Since, the number of clients are increasing, which give arise to a lot of problems like increased interference, complexity and significant amount of power consumption in the processing and transmission. This paper investigates potential improvements in power optimization by modifying the classical macro-cell with massive multiple input multiple output at the mobile tower, which is overlaid with small cell access points. The main aim of the paper is to optimize the utilization of energy, while maintaining the quality of service at the client end and power optimization at the small cell access point, and base station. But along with power optimization, complexity is also a prime objective of concern. Hence for optimizing or minimizing the power, while maintaining low complexity, a new low complexity algorithm is proposed and is compared with a classical relaxed zero-forcing beam forming algorithm and the optimal solution cases. The complexity analysis of this proposed approach has been done on the basis of change in the base stations and the number of UEs surrounding it. The potential merits of this proposed approach for different deployment scenarios, such as an urban macro heterogeneous deployment scenario in the 3GPP LTE Standard and an urban macro, sub-urban macro, and rural macro deployment scenario in the ITU-R M.2135 standard are analyzed by numerical calculations.

An Admission Control Mechanism for 5G LWA

To alleviate the spectrum scarcity problem in fifth-generation (5G) networks, traditional mobile data offloading schemes from long term evolution (LTE) to wireless local area networks (WLANs) have been revised by the third-generation partnership project (3GPP) in release 13, which is known as LTE-WLAN aggregation (LWA). With LWA, user equipment units (UEs) supporting both LTE and WLAN can utilize both LTE and WLAN links simultaneously. Thus, UEs under the coverage of an LWA network will be surrounded by multiple standards, such as LTE, WLAN, and LWA, along with cells of different sizes and coverage. Providing the LWA service to all UEs unconditionally may lead to serious intra-cell unfairness, degradation of system-level quality of service (QoS), and a reduction in system resource utilization. Hence, to resolve this issue, two important challenges need to be addressed: Which LTE UEs should be transferred, and how many LTE UEs need to be transferred. In this paper, we propose a user-offloading algorithm for evolved node B (eNB) hardware that smartly allocates the deprived LTE UEs and assigns the LWA service to an optimal number of UEs without degrading the QoS for existing WLAN UEs. With this proposed scheme, all LWA-preferred UEs with poor LTE performance and a good WLAN condition have the opportunity to access LWA service to improve performance. We show that the proposed scheme maximizes the throughput performance of the whole network.

V2X를 위한 향상된 랜덤 자원 선택 기술

V2X 통신에서, 사이드링크 수신 능력들이 없는 디바이스들 지원하기 위한 경우 및 단말의 파워 소비 감소가 요구되는 경우를 고려하여 랜덤 기반의 자원 선택 방식이 요구된다. 본 논문에서는 PSCCH 주기 내에서의 데이터를 위한 서브프레임 풀에 대하여 하나의 TRP를 반복 적용하는 D2D에서의 자원 선택 방식을 개선하여, 보다 향상된 랜덤 자원 선택 방식을 위해 단말-특정한 시드 값을 가지는 의사-랜덤 시퀀스를 바탕으로 TRP가 매 적용마다 달리 적용되는 방식을 제안하였다. 수치 분석을 통해 제안된 기술의 성능을 분석한 결과, 데이터 TB을 위해 각 단말에게 할당된 자원들 간의 충돌 확률이 줄어들며 이를 통해 자원 출동을 최대한 피하면서 동시에 자원할당이 가능한 단말의 개수를 늘릴 수 있는 것을 확인할 수 있었다. In V2X communication, a random based resource selection scheme is needed with considerations of cases that support devices without sidelink reception capabilities and require reduction of UE's power consumption. In this paper, as improvement of D2D's resource section scheme that one TRP is repeated to data subframe pool within a PSCCH period, it is proposed that different TRPs is applied for enhanced random resource selection based on pseudo-random sequence having UE-specific seed value. By results of proposed scheme's performance by numerical analysis, it is confirmed that collision probability among resources allocated to each UE for data TB is reduced, and a number of UEs which can avoid resource collision as much as possible and have simultaneous resource allocation is increased.

Hybrid user association for maximising energy efficiency in heterogeneous networks with human‐to‐human/machine‐to‐machine coexistence

In this study, a hybrid user association scheme for maximising energy efficiency is proposed in a wireless uplink heterogeneous network with human-to-human and machine-to-machine communications coexistence. Different from conventional user association algorithms, the authors consider access control protocol for both the human-type-communications (HTCs) users equipments’ (UEs) and machine-type-communications (MTCs) UEs according to their characteristics during user association phase, i.e. a contention-free access mechanism for HTC UEs and a random access based on access class barring mechanism for MTC UEs. They formulate the user association problem as a maximisation of the overall UEs’ energy efficiency in consideration of both the HTC and MTC UEs’ quality of service (QoS) guarantees and load balance among base stations simultaneously. To solve the problem, they propose a distributed iterative algorithm which adopts both the matching theory and the dual decomposition theory, and prove its convergence. Finally, simulation results show that their proposed user association scheme not only outperforms existing schemes in terms of the load balance and the overall energy efficiency but also achieves the same performance as exhaustive search in the case of less number of UEs, while satisfying both the HTC and MTC UEs’ QoS requirements.

Performance Analysis of FLS, EXP, LOG and M-LWDF Packet Scheduling Algorithms in Downlink 3GPP LTE System

Long-Term Evolution (LTE), an emerging and promising fourth generation mobile technology, is expected to offer ubiquitous broadband access to the mobile subscribers. In this paper, the performance of Frame Level Scheduler (FLS), Exponential (EXP) rule, Logarithmic (LOG) rule and Maximum-Largest Weighted Delay First (M-LWDF) packet scheduling algorithms has been studied in the downlink 3GPP LTE cellular network. To this aim, a single cell with interference scenario has been considered. The performance evaluation is made by varying the number of UEs ranging from 10 to 50 (Case 1) and user speed in the range of [3, 120] km/h (Case 2). Results show that while the number of UEs and user speed increases, the performance of the considered scheduling schemes degrades and in both case FLS outperforms other three schemes in terms of several performance indexes such as average throughput, packet loss ratio (PLR), packet delay and fairness index.

Polycentric Patterns and Housing Affordability: Does a Relationship Exist?

Polycentric structures are one of the possible kinds of territorial organization for human settlements. They have recently become important because they have been recommended by a number of UE documents as the most suitable structure for attaining equilibrium in economic, social, and territorial development. This paper seeks to verify the possible advantages of the polycentric model empirically for the case of a typical urban problem such as housing affordability. The empirical analysis is carried out on Italian administrative regions, through the construction of a regional index of polycentrism and an analysis of the level and territorial variability of house prices. Il policentrismo e la modalita insediativa piu studiata degli ultimi anni, vuoi perche esso corrisponde a molte strutture urbane del contesto europeo, vuoi perche e stato assunto dall’Unione Europea come obiettivo di politica territoriale. I vantaggi del policentrismo, spesso indicati in sede teorica piu che empiricamente rilevati, sembrano essere numerosi ed esso e indicato come un modello di sviluppo territoriale piu equilibrato rispetto sia al tradizionale assetto monocentrico, sia al piu recente fenomeno dello sprawl. L’obiettivo del presente saggio e di verificare empiricamente la superiorita del modello policentrico in relazione ad un problema tipicamente urbano quale quello dell’accessibilita della casa.