Non-terrestrial networks (NTNs) are a key feature to be supported in the next-generation mobile network. The contention-based 2-step (grant-free) and 4-step (grant-based) random access (RA) procedures used in existing terrestrial networks will be adopted in NTNs. In applying the 2-step and 4-step RA in NTNs, the preamble configuration is a critical factor affecting the performance of the random access channel (RACH). In this paper, we present a general system model to investigate the impact of preamble configuration and the RACH parameters of the 2-step and 4-step RAs (i.e, random access response (RAR) window size, maximum transmission time, and back-off window size) on the access success probability, average access delay, and the use of resources under different offered loads. Simulations were conducted to investigate the pros and cons of 2-step and 4-step RAs under various conditions.

Access parameters, user equipment (UE) density, system load, and channel conditions significantly impact the performance of random-access (RA) protocols, influencing network capacity, latency, and robustness. In 3GPP standard, the prach-ConfigurationIndex access parameter is used to designate reserved RA channel occasions (ROs) for each beam, enabling UEs to derive beam mapping patterns and select desired beams through a beam-based RA protocol. This article addresses the challenge of bursty arrivals from massive Internet of Things (IoT) devices with sporadic traffic patterns in 5G beamforming networks. We propose an analytical model to evaluate the performance of the beam-based RA protocol for any beam mapping pattern. Extensive computer simulations are conducted to validate the accuracy and effectiveness of our model across various scenarios. The results demonstrate that our model provides valuable insights into the behavior and performance of the beam-based RA protocol and offers a reliable tool to evaluate and optimize beam mapping patterns in practical 5G network deployments.

Open radio access network (O-RAN) introduces a new architecture with new components and interfaces, which suffers from numerous security challenges and risks. The C-Plane denial-of-service (DoS) attack is considered one of the security threats for O-RAN fronthaul interface (FHI) [6]. In this paper, we develop a software tool named 'C-Plane DoS Attacker' to conduct the C-Plane DoS attack for O-RAN FHI. The effectiveness of the proposed C-Plane DoS Attacker is verified on top of a DU-RU testbed developed based on the source code provided by the O-RAN Software Community (OSC).

Narrowband Internet of Things (NB-IoT) is a new technology developed to support low-power wide area networks (LPWAN) services. To extend its coverage and decrease its transmission power, devices in one NB-IoT cell are divided into several coverage enhancement (CE) levels with different random access configuration. This potentially results in unfair access, especially when massive number of devices in different CE levels simultaneously accessing the network. This work presents an effective strategy to configure the random access in NB-IoT to yield fair performance across CE levels. An analytical model is used to estimate the performance of each CE level and overall system performance in term of normalized throughput and average access delay. Simulation is incorporated to verify the accuracy of the model. Different practical assumptions of fair system are explored and examined in the experiment. The result shows that the analytical model is accurate under various loads. Additionally, the proposed search strategy is proven to be able to obtain the configuration which yield acceptable throughput fairly for all CE levels.

Narrowband Internet-of-Things (NB-IoT) is one of the major access technologies proposed to support massive machine type communications (mMTC) services for the 5thgeneration (5G) mobile networks. Many emerging services and networking paradigms are expected to be developed on top of NB-IoT networks. This paper summarizes the steps required to build up an open source narrowband Internet-of-Things (NB-IoT) network. This work is a joint research and development (R&D) result from industry and academic collaboration. The open source NB-IoT enhanced Node B (eNB) is jointly developed by EURECOM, B-COM and NTUST based on the well-known OpenAirInterface TM(OAI) open source Long-Term Evolution (LTE) eNB. The NB-IoT eNB is successfully connected to an evolved packet core (EPC) developed by Nokia Bell Lab. We demonstrate how to use commercial off-the-shelf (COTS) NB-IoT module to forward its sensing data to the Internet via the open source NB-IoT network.

5G networks generate massive (quasi-) real-time data streams that different network apps can exploit to implement sophisticated single- or cross-domain control and management logic. This paper presents ElasticSDK, a Software Development Kit specially designed to abstract the development and chaining of such agile 5G monitoring apps for the control, management, and coordination of the underlying 5G network heterogeneous modules. Custom apps can collect, incrementally process and further expose flows in a flexible Pub/Sub fashion via appropriate SDK API calls, thus sharing both raw and complex data flows among themselves. Furthermore, the design of ElasticSDK allows respecting typical 5G data ownership and privacy models, as desired by the different 5G stakeholders ranging from physical infrastructure providers up to service providers over slicing. Finally, we provide two important contributions to the 5G open-source research community: (i) a RAN monitoring prototype implementation over the ElasticSearch and FlexRAN platforms that allows to demonstrate ElasticSDK app development and capturing hierarchical control features of typical SDN-enabled 5G architectures, and (ii) a first-ever publicly available dataset of realistic 5G RAN monitoring traces.

Cellular Internet of Things (C-IoT) is a new term referring to access technology introduced by 3GPP to support IoT applications. C-IoT has several advantages compared to the unlicensed low-power wide area (LPWA) technology. However, C-IoT's random access (RA) procedure is easily overloaded by massive access from IoT applications. This article proposes a novel mechanism which combines a simple algorithm to assess the instantaneous load and a dynamic tuning of the contention level on the third message of RA. The technical consideration for integrating our mechanism to the existing C-IoT system is also presented. Performance evaluation is conducted under several practical scenarios. The results show that our proposed mechanism brings a significant increase of normalized throughput with the cost of just a slight increase of the access delay compared to the original system. Additional performance comparisons with the other existing approaches which target similar problem are also included. The results show that our mechanism performs well, especially when considering how simple it is to be implemented.

LoRaWAN is a promising solution of Low-power wide area network (LPWAN) operating in unlicensed spectrum to support long range wireless services for Internet of Things (IoTs). However, with the growth of IoT devices deployed in a fixed geographic area, the immunity to interference on the communication increases significantly. Attackers may utilize such situation to jam packet transmission by emitting RF interference signal at the same time when a LoRa end node is sending data to the LoRa gateway. As a consequence, the transmission of the LoRa end node would fail due to collision which would in turn reduce the network performance. In this paper, we implement a LoRa jammer on commercial LoRa devices by modifying the open source and figure out the proper setting of the jammer through three scenarios aiming to evaluate the influence of LoRa transmission configuration on jamming performance. Specifically, the impact of non-orthogonality of LoRa transmission on jamming effect is investigated. Possible countermeasures for LoRaWAN are then presented to alleviate the jamming attacks.

Narrowband Internet of Things (NB-IoT) is a cellular standard supporting IoT applications in wide area. NB-IoT utilizes “repetition” to extend the coverage of the base station. The repetition value in NB-IoT physical random access channel (NPRACH) is set to ensure 99% detection probability without considering the inherent “retransmission” nature of NPRACH. In this paper, we try to optimally trade extra time-diversity gain in preamble transmission obtained from retransmission to reduce the repetition requirement in NB-IoT. The preferred regions for pure repetition and retransmission schemes sharing the same amount of NPRACH resource under various offered loads and channel conditions are first investigated. The optimal amount of NPRACH resource, repetition value, and retransmission value are then obtained subject to a target successful probability. The results show that the embedded retransmission nature of NPRACH can effectively reduce the number of repetitions. High number of repetitions is required only under worse channel condition.

Simultaneous random access attempts from massive machine-type communications (mMTC) devices may severely congest a shared physical random access channel (PRACH) in mobile networks. This paper presents a novel two-phase random access (TPRA) procedure to deal with the congestion caused by mMTC devices accessing the PRACH. During the first phase, the TPRA splits the mMTC devices into smaller groups according to a preamble selected randomly by the devices. Then, in the second phase, each group of devices is assigned with a dedicated channel to complete the random access procedure. The proposed concept allows a base station to adjust the number of dedicated channels in real-time according to the actual network load. We then present an analytical model to estimate the access success probability and the average access delay of the TPRA. Finally, we propose a simple formula to determine the optimal number of random access resources for the second phase of the proposed TPRA. Simulations are carried out to validate the analytical models and to demonstrate the benefits of the TPRA compared to competitive techniques.

Narrowband Internet of Things is a new access technology introduced by 3GPP. This paper presents an analytical model to estimate the access success probability and average access delay of the random access channels by considering maximum number of preamble transmissions, size of backoff windows, and number of subcarriers in each coverage enhancement levels. A joint optimization technique is proposed to configure the parameters to maximize the access success probability under a target delay constraint. The accuracy of the analysis and the effectiveness of the proposed optimization technique are verified by computer simulations and benchmarked with exhaustive search. The result shows that the proposed optimization is able to find the optimal configuration under various conditions.

Narrowband Internet of Things (NB-IoT) is a new access technology introduced by 3GPP. It aims to support massive machine-type communications services in wide area. This work presents an analytical model to estimate access success probability and average access delay of random access (RA) procedure for three coverage enhancement (CE) levels in NB-IoT. The behavior of RA procedure in NB-IoT is analyzed and accuracy of the analysis is verified by computer simulations.

Due to the random access (RA) process, machine-type communication (MTC) devices of a group may delay until the time point of the next polling of another groups and lead to a serious access delay problem. To solve this problem, in this paper, we investigate a dynamic backoff indicator (BI) assignment (DBA) algorithm that lets the delayed MTC devices speed up to finish their RA within an expected period of time. The proposed method also realizes the crucial concept of cyber-physical systems (CPS). Simulation results and analyses validate the effects of CPS on reducing collision probability in large-scale MTC.

A group of multi-mode wearable devices or mobile terminals (MTs) may be carried by the same vehicle and then perform group handover during the movement within heterogeneous networks. However, it is a challenging work to determine a proper target network which is good for both MTs and the network provider. This paper presents a simulated-annealing-based group handover decision scheme to reduce the group handover blocking ratio, decrease the number of handover, balance the traffic load between networks, and ensure the target quality of service (QoS) requirements of MTs. Simulation results show that the proposed scheme can reduce the group handover blocking ratio efficiently and balance the load. Besides, when the number of group MTs is not quite large, the number of handover can be reduced and the QoS requirements can be fulfilled.

The performance of contention-based access mechanism mainly depends on the resource allocation. This paper presents a generalized resource allocation scheme to support access prioritization in a multichannel slotted ALOHA system. The proposed scheme has great usability as it can be implemented in any similar mechanism such as OFDMA, which is used in LTE and beyond. We simulate its access-success probability and access delay in a one-shot random access attempt. The result demonstrates that the scheme can be used to represent any resource allocation schemes, such as dedicated, shared, partially-shared, as well as arbitrary resource allocation.

Group paging is one of the solutions proposed to deal with the radio access network (RAN) overload problem resulted from bursty machine-type communications (MTC) traffic in long-term evolution-advanced (LTE-A) networks. In group paging, the base station normally reserves a fixed amount of random access opportunities (RAOs) for the grouped users to perform random access (RA) during a paging access interval. However, the number of contending users is quickly decreased and thus, static allocation of RAOs is not efficient. This paper presents a dynamic resource allocation (DRA) scheme which dynamically adjusts the reserved RAOs for group paging based on the estimated number of contending users in each RA slot. Simulation results demonstrate that, compared with the traditional static allocation scheme, the proposed DRA scheme can improve the utilization of RAOs by 9% under a target access success probability constraint of 90%.

Simultaneous channel accesses from mass machine-type communications (MTC) devices may congest the random-access channels (RACHs) of LTE-A networks. Currently, 3GPP selects extended access barring (EAB) mechanism as the baseline solution to relieve the congestion of RACHs by barring low-priority devices. Different settings of EAB parameters may re-shape the arrival process of MTC traffic and thus, lead to unpredictable performance. This paper presents an analytical model to investigate the performance of the EAB algorithm on the RACHs in LTE-A networks. Computer simulations were conducted to verify the accuracy of the analysis. The optimal values of paging cycle and repetition period of system information block type 14 (SIB14) can then be obtained from the analytical model subject to a target quality-of-service (QoS) constraint.

Random access channels (RACHs) in cellular networks are normally designed for Poisson-distributed arrivals with a constant rate. Unexpected bursty arrivals may result in severe collisions in RACHs and thus degrade users' service qualities. This paper presents an analytical model for investigating the transient behavior of the RACHs with bursty arrivals generated in a specific time interval for orthogonal frequency-division multiple access (OFDMA) wireless networks. The proposed model has considered the implementation details of the OFDMA random access procedure (such as periodic access characteristic, uniform random backoff policy, and power-ramping effect) and the effect of new arrivals. The performance metrics of collision probability, success probability, and average access delay and the cumulative distribution function of the number of preamble transmissions and access delay for the successfully accessed mobile station are then derived based on the analytical model. The accuracy of the proposed analytical model was verified through computer simulations, and the results show the effectiveness of the proposed model.

Current heterogeneous wireless networks often overlap because of their complementary characteristics and the large deployment of various wireless access technologies. Mobile devices, which are equipped with multiple wireless interfaces, called multiple radio access technologies (multi-RATs) mobile stations (MSs), are also becoming increasingly popular. Therefore, common radio resource management (CRRM) has been proposed to coordinate heterogeneous radio resource allocations and improve the resource utilization of heterogeneous wireless networks. However, CRRM is an NP-hard problem, and low-complexity approaches for dynamic resource management are in high demand. In this paper, the resource request and allocation between multi-RAT MSs and heterogeneous wireless networks are modeled as a directed graph. Thus, the problem of searching for feasible radio resource allocations is simplified to finding trees in a directed graph. Based on the proposed model, a heuristic scheme can be used to find a feasible solution efficiently, and dynamically adjust the workload of heterogeneous BSs to accommodate new requests. Experimental results demonstrate that the heuristic scheme can reduce the request reject rate by 10%-55% compared with conventional approaches.

Random access channels (RACHs) in cellular networks are normally designed for Poisson-distributed arrivals with a constant rate. Unexpected bursty arrivals may result in severely collisions in RACHs and thus, degrade users' service qualities. This paper presents an analytical model to investigate the transient behavior of the RACHs with bursty arrivals generated in a specific time interval in OFDMA wireless networks. The proposed model considers the effect of new arrivals and the real-world implementation constraints of the OFDMA random access procedure such as periodic access characteristic, uniform random backoff policy, and power-ramping effect. The average number of contending and success mobile stations (MSs) in each random-access slot are then derived using the proposed model. The accuracy of the proposed model was verified through computer simulations and the results show the accuracy of the analysis.

Group paging is one of the mechanisms proposed to resolve the radio access network (RAN) overload problem resulted from simultaneous channel access from huge machine devices [1]. This paper presents a consecutive group paging to enhance the performance of group paging. In consecutive group paging, the base station reserves multiple paging cycles to page the same group of users consecutively such that UEs which failed in the earlier paging cycles can perform random-access procedure again in the later paging cycles. We utilize the analytical model presented in [2] to derive the performance metrics of consecutive group paging. The optimal group size, total number of reserved radio resource and the maximum number of preamble transmission are derived for each value of paging cycle threshold. The accuracy of the proposed analytical model is verified via computer simulations. Simulation results demonstrate that the proposed consecutive group paging enhances the performance of group paging.

Relaying technology is a cost-effective solution for achieving throughput enhancement for cell-edge users or extending the cell coverage for the 3GPP LTE-A systems. In this study, we investigate the flow control scheme in the LTE-A relay networks employing the Type-I relay nodes (RNs). However, the buffer-overflow problem [7, 8] caused by high-speed arrival traffic and the handover forwarding problem caused by UE's handover are two main issues that affect the performance of 3GPP LTE-A relay networks. To mitigate these problems, we present a dynamic two-threshold flow control scheme (DTFCS) which can dynamically adjust the upper buffer-threshold of RN based on the channel quality. Results showed that DTFCS can reduce 40% of the total number of forwarding packets during the handover when compared with the two-threshold flow control scheme. Additionally, when the proposed scheme is compared to single-threshold flow control scheme, DTFCS excels by imposing much less signaling overhead on the expense of a slight increase in the number of forwarding packets.

In [1], the throughput and access delay performance of the RACH in an orthogonal frequency division multiple access (OFDMA) system is analyzed. However, the analysis of access delay is incorrect. This note corrects the original equations and results show that the new equations correct the non-negligible error of the average access delay under the uniform backoff policy.

This paper summarizes the two definitions of the collision probability from the perspective of an MTC device and an RAO were presented in 3GPP TR 37.868. We use the results presented in TR 37.868 to show the inconsistency between the two definitions. It worth to note that the researcher needs to clearly specify the definition they used in presenting the results of their proposed radio access network overload control schemes. This paper further presents an analytical model to derive the collision probability, the success probability, and the idle probability based on the two definitions.

A CDMA-based common channel is a shared uplink channel that multiple users may send their event- specific CDMA codes to indicate their status. In such a channel, the base station may fail to detect a transmitted CDMA code due to the channel fading effect and the multiple access interference (MAI) resulting from the simultaneous transmission of the other CDMA codes. This paper presents system architecture to detect the transmitted CDMA codes in a CDMA-based common channel. A dynamic-threshold- setting method is presented to reduce the detection time and maximize the detection probability. A selective-retransmission method is further proposed to enhance the detection probability by exploring the time-diversity gain. Simulations results showed the proposed method may reduce the number of required radio resource units and achieve a low detection error probability than conventional methods. Hence, it could be a potential solution to reduce huge uplink singling overhead resulted from the simultaneous feedbacks from all multicast/broadcast subscribers.

Multicast and broadcast service (MBS) is one of the important services for next generation wireless systems. Normally, the base station (BS) may perform advance radio resource management functionalities based on the channel quality indicator (CQI) reports sent by MBS subscribers. However, the CQI reports lead to high signaling overhead at the uplink. This paper proposed a common feedback channel to reduce the uplink signaling overhead. A simple dynamic modulation and coding scheme (MCS) is then presented to improve the spectral efficiency based on the limited information carried by the common feedback channel. Simulation results showed that the proposed method could enhance the spectral efficiency with reduced signaling overhead. The results also demonstrated the robustness of the common feedback channel in the presence of feedback errors.

A human centric communication network (HCCN) is a communication network offering human centric (or, social-network-based) mobile Internet services. This paper proposes a three-layer network architecture to model the relationship among users, their social groups, and the serving radio access networks for HCCN. Based on this model, several advertising techniques in HCCN are investigated. Simulation results showed the effectiveness of four algorithms in different application scenarios.

Relay is one of the key technologies used by both the Third Generation Partnership Project (3GPP) Long Term Evolution-Advanced (LTE-Advanced) and IEEE 802.16m to ameliorate cell edge throughput. Despite the throughput enhancement achieved by deploying relay stations (RSs), wireless systems supporting relay are vulnerable to frequent handoffs, which deteriorate the dropping performance of realtime communications. This paper proposes a mathematical model to appraise the dropping performance of the eNB-first channel access policy in LTE-Advanced relay networks. The eNB-first policy prefers an eNB-channel over a RS-channel when determining an access channel for a new and a handoff call. Closed-form analytical result is obtained for the dropping probability of the eNB-first policy and based on the result a numerical study is conducted to evaluate the influences of various parameters on the dropping performance. The result developed in this paper can be used to adjust the call admission control strategies to get acceptable dropping performance in LTE-Advanced relay networks.

It is not easy to achieve real-time video transmission testbed on WiMax, due to the lack availability of WiMax networks. This paper presents a ns-2 based emulator to evaluate the quality of multicast video services transmitted over an IEEE 802.16 wireless network. The impact of the modulation schemes and the cyclic prefix, on the throughput and video quality were discussed and the performance of the proposed emulator was evaluated. Specially, the results about the emulator's performance are relevant when real-time services are taken into account. The main contribution in this paper is the general guidelines provided to develop an efficient real-time multicast streaming video testbed on wireless networks, exploiting the potentialities of a tool as ns-2.

It has been shown that IEEE 802.11 DCF medium access control (MAC) protocol may not be suitable for multihop wireless networks due to its relatively low throughput and severely unfairness problems. A tokenpassing MAC protocol, named Ripple, has been proposed to enhance the throughput of DCF by utilizing spatial reuse. However, two perfect assumptions of dasiafixed-length data packetpsila and dasiaidentical interference range and transmission rangepsila in Ripple make it less practical in the real world. This paper proposes an Enhanced Ripple (E-Ripple) protocol aiming to remove the two restrictions. An analytical model is presented to estimate the performance of E-Ripple and the accuracy of the analysis is then verified via computer simulations. The results indicate that E-Ripple performs well in such a non-perfect environment.

A multi-hop wireless metropolitan area network (WMAN) is a metropolitan area network that adopts the wireless multi-hop technique to provide high-speed data link between adjacent nodes for metropolitan area. This work presents an improved wireless token ring (IWTRP) protocol for W-MAN. IWTRP adopts the concept of spatial reuse to enhance the throughput of the W-MAN via using multiple tokens. It provides mechanisms to enable multi-token circulation within a ring and to prevent from the possible packet collisions. An analytical model is further proposed to derive the per-node saturation throughput of the W-MAN. Simulation results demonstrate the accuracy of the analysis and the superiority of IWTRP

A common problem of a multi-hop wireless backhaul network (WBN) is the end-to-end throughput of a relay node is location-dependent. That is, the closest relay node to the gateway will get the most bandwidth. This paper presents a location-independent scheduling mechanism (LISM) for WBNs. LISM adopts a simple time-stamp-based approach to resolve the location-dependent problem and utilizes a dual-queue approach to minimize the sorting complexity. Simulation results indicate that LISM successfully solves the location-dependent problem.

This work presents a power-strength-based selective forwarding (PSF) mechanism to efficiently flood route requests (RREQs) during route discovery in multihop cellular networks (MCNs). In PSF, each mobile station utilizes the received power-strength, instead of connectivity or overheard information, to determine itself whether to be a forwarding participant or not. It reduces the signaling overhead and prevent unnecessary interference during the route discovery. An analytical method is proposed to set the power thresholds required to ensure a given connectivity probability. The accuracy of the proposed method has been verified via computer simulation. The results show that the proposed PSF mechanism can significantly reduce the number of RREQs while ensuring the connectivity probability.

A common problem of a multi-hop wireless backhaul network (WBN) is the end-to-end throughput of a relay node is location-dependent. That is, the closest relay node to the gateway gets the most bandwidth. The location-dependent problem may be solved by adopting the concept of virtual-timestamp-based scheduling. This paper presents a queueing model to analyze the performance of the proposed concept. The accuracy of the analysis is verified via computer simulation. Simulation results indicate the accuracy of the analysis and the effectiveness of the proposed concept.

This paper proposes a maximum freedom last (MFL) scheduling algorithm for downlinks, from the roadside unit to the onboard unit (OBU), of dedicated short-range communication networks in intelligent transportation systems, to minimize the system handoff rate under the maximum tolerable delay constraint. The MFL scheduling algorithm schedules the service ordering of OBUs according to their degree of freedom, which is determined by factors such as remaining dwell time of service channel, remaining transmission time, queueing delay, and maximum tolerable delay. The algorithm gives the smallest chance of service to the OBU with the largest remaining dwell time, the smallest remaining transmission time, and the largest weighting factor, which is a function of the queueing delay and the maximum tolerable delay. Simulation results show that the MFL scheduling algorithm outperforms the traditional first-come-first-serve and earliest-deadline-first methods in terms of service failure and system handoff rates

Wireless mesh network, a new wireless broadband access technology, is currently attracting significant attention. This work proposes a distributed medium access protocol, named Ripple, for wireless mesh networks (WMNs) under tree topology. In contrast to existing random-access approaches, Ripple uses a controlled-access approach to protect nodes from unintentional packet collisions and maximize the spatial reuse. The performance of Ripple under an error-free channel was investigated and the accuracy of the analysis was verified by simulation. Simulation results also indicated that Ripple achieved throughput, stability, and QoS enhancement than that of 802.11 DCF under a highly loaded situation in both chain and tree topologies.

This work presents a new scheme which exploits differentiations of both inter frame space (IFS) and contention window (CW) to achieve weighted fairness for two classes of services under enhanced distributed channel access (EDCA) mode in an 802.11e WLAN. Given the arbitration IFSs (AIFSs), the proposed scheme can properly set the corresponding CWs such that the ratio of the two classes' successful transmission probabilities can attain a pre-defined weighted-fairness goal. Additionally, the throughput and delay of the two classes of services are derived. The simulation results compare well with the analytical results. Also, the analytical results illustrate that the proposed scheme can achieve a fairness index very close to 1 and attain a greater aggregate throughput with lower collision probability than the CW differentiation scheme presented in A. Banchs and X. Perez (2002), for a specified weighted-fairness goal.

In this paper, we propose a QoS-aware power-strength classified packet scheduling (PCPS) scheme that can classify the transmission power-strength of a VBR connection into several classes and determine the admitted service rate of each class at connection setup time. During the transmission time of each connection, PCPS scheme can dynamically adjust the downlink service rate of each connection in accordance with the admitted service rate of the current transmission power-strength class while retaining all connection's frame error rate requirements. With this power-strength classified scheduling, PCPS scheme can decrease the average packet delay and increase the bandwidth utilization. Furthermore, a two-stage scheduling architecture is also employed to reduce the scheduling complexity resulted from simultaneous adjustment of both service rate and transmission power-strength in WCDMA. Performance results show that the delay bound and the packet loss ratio of a VBR connection can be guaranteed.

We present a traffic-scheduling framework that can dynamically allocate radio resources to a general packet radio service (GPRS) mobile station (MS) based on the interference levels of the radio links and the quality of service (QoS) specification of the MS. The underlying idea of this scheduling scheme is to preserve more bandwidth for use by those MSs that are within a low interference region so that the limited radio resources can be used more effectively. In this scheme, an MS uses a low transmission rate for data transfer when the MS is within a high interference region to avoid wasting bandwidth by transmitting data in a condition with high interference. In order to compensate for the service loss of the MS, we allocate more bandwidth to the MS when it is within a low interference region. In addition, we also propose an analytical model that can be used to derive the transmission rate for an MS in a low interference region based on the delay-bound requirement of the MS. The performance results show that our dynamic scheme can utilize the bandwidth more effectively to satisfy various QoS requirements of the MSs in the GPRS system without changing the convolution-coding rate.

This paper proposes a neural fuzzy approach for connection admission control (CAC) with QoS guarantee in multimedia high-speed networks. Fuzzy logic systems have been successfully applied to deal with traffic-control-related problems and have provided a robust mathematical framework for dealing with real-world imprecision. However, there is no clear and general technique to map domain knowledge on traffic control onto the parameters of a fuzzy logic system. Neural networks have learning and adaptive capabilities that can be used to construct intelligent computational algorithms for traffic control. However, the knowledge embodied in conventional methods is difficult to incorporate into the design of neural networks. The proposed neural fuzzy connection admission control (NFCAC) scheme is an integrated method that combines the linguistic control capabilities of a fuzzy logic controller and the learning abilities of a neural network. It is an intelligent implementation so that it can provide a robust framework to mimic experts' knowledge embodied in existing traffic control techniques and can construct efficient computational algorithms for traffic control. We properly choose input variables and design the rule structure for the NFCAC controller so that it can have robust operation even under dynamic environments. Simulation results show that compared with a conventional effective-bandwidth-based CAC, a fuzzy-logic-based CAC, and a neural-net-based CAC, the proposed NFCAC can achieve superior system utilization, high learning speed, and simple design procedure, while keeping the QoS contract.

This paper presents the design of a fuzzy usage parameter controller (FUPC) for ATM (asynchronous transfer mode) networks. The usage parameter control (UPC) is here based on a dual leaky bucket (DLB) mechanism, with parameters of token generation rate and token pool size. In FUPC, we further employ parameters of token-change rate and interarrival time of incoming cells as input linguistic variables to reflect the usage situation in advance. Simulation results reveal that the proposed FUPC possesses a shorter response time to detect violation cells, keeps the output rate of the user close to the declared usage parameters, and thus achieves more precise control than DLB.

ATM (asynchronous transfer mode) networks support services with bursty traffic. A sophisticated and real-time admission controller is needed not only to guarantee the required quality-of-service (QoS) for existing calls but also to achieve higher system efficiency. In this paper, we propose a power-spectrum based neural fuzzy connection admission control (PNFCAC) mechanism for an ATM network. The power spectrum of the input process explicitly describes the correlation behavior of input traffic and has a great impact on the queueing behavior of an ATM network. The neural fuzzy controller has been successfully applied to deal with the complex problem which can not be analyzed by classical methods based on probability theory and bivalent logic. Under the constraint of QoS, we construct a decision hyperplane of connection admission control according to the parameters of the power spectrum. We further adopt the learning/adapting capabilities of the neural network to adjust the optimum location of the boundary between these two decision spaces. Simulation results show that the PNFCAC mechanism provides a superior system utilization over the conventional CAC schemes and the neural fuzzy CAC using time-domain analysis, while keeping the QoS contract.

ATM (asynchronous transfer mode) systems can support services with bursty traffic. An ATM system needs a sophisticated and real-time connection admission controller not only to guarantee the required quality-of-service (QoS) for existing calls but also to raise the system efficiency. The input process has a power-spectral-density (PSD) which explicitly contains the correlation behavior of input traffic and has a great impact on the system performance. Also, a neural network has been widely applied to deal with traffic control related problems in ATM systems because of its self-learning capability. We propose a PSD-based neural-net connection admission control (PNCAC) method for an ATM system. Under the QoS constraint, we construct a decision hyperplane of the connection admission control according to parameters of the power spectrum. We further adopt the learning/adapting capabilities of the neural network to adjust the optimum location of the boundary between these two decision spaces. Simulation results show that the PNCAC method provides a superior system utilization over the conventional CAC schemes by as much as 18%, while keeping the QoS contract.

This paper proposes a neural fuzzy connection admission control (NFCAC) scheme, which combines benefits of fuzzy logic controller and learning abilities of the neural-net, to solve the connection admission control (CAC) problems in ATM networks. Fuzzy logic systems have been successfully applied to deal with the traffic control related problems and provided a robust mathematical framework for dealing with "real-world" imprecision; multilayer neural networks are capable of producing complex decisions with arbitrarily nonlinear boundaries and they have been used as a solution for CAC. However, the application of a neural network or a fuzzy logic system to CAC presents some difficulties in a real system operation. The proposed NFCAC solves the difficulties by combining the benefits of the existing traffic control mechanisms, linguistic control strategy of the fuzzy logic controller and the learning ability of the neural net. Simulation results show that the proposed NFCAC saves a large amount of training time and simplifies the design procedure of a CAC controller but provides a superior system utilization, while keeping the QoS contract, than either the neural network or fuzzy logic system does.

This paper presents the design of a fuzzy traffic controller that simultaneously manages congestion control and call admission control for asynchronous transfer mode (ATM) networks. The fuzzy traffic controller is a fuzzy implementation of the two-threshold congestion control method and the equivalent capacity admission control method extensively studied in the literature. It is an improved, intelligent implementation that not only utilizes the mathematical formulation of classical control but also mimics the expert knowledge of traffic control. We appropriately choose input linguistic variables of the fuzzy traffic controller so that the controller is a closed-loop system with stable and robust operation. We extract knowledge of conventional control methods from numerous analytical data using a clustering technique and then use this knowledge to set parameters of the membership functions and fuzzy control rules via fuzzy set manipulation (linguistically stated but mathematically treated) with the aid of an optimization technique named genetic algorithm (GA). Simulation results show that the proposed fuzzy admission control improves system utilization by a significant 11%, while maintaining the quality of service (QoS) contract comparable with that of the conventional equivalent capacity method. The performance of the proposed fuzzy congestion control method is also 4% better than that of the conventional two-threshold congestion control method.

Due to the demand for high-speed and multimedia services, ATM (asynchronous transfer mode) networks have increasingly received high attention. The multimedia services in ATM networks have diverse traffic characteristics and service requirements, appropriate traffic controls of call admission and congestion are needed so as to guarantee the required quality of service (QOS) for services. Previous studies on the traffic control were based on the results of queueing analyses. In the present paper, an alternative traffic control for admission in conjunction with congestion based on fuzzy set theory are proposed for an ATM network. The performance evaluation via simulation shows the effectiveness of the proposed method in comparison with the equivalent capacity in Guerin et al. (1991); link utilization is effectively improved by 8% while keeping the QOS contract.>