The prediction criterion is based on signal-to-interference ratio (SIR) measurements of the received signal at each mobile user; we then use a finite state Markov chain (FSMC) model for predicting the future state of the wireless channel. Department of Information and Communication Systems Engineering of the University of the Aegean for offering me the opportunity for this PhD study.
Introduction
- Introduction
- The Need for Cross-Layer Techniques
- Objectives, Motivations, and Scope of the Thesis
- Organization of The Thesis
The proposed cross-layer framework consists of the prediction criterion and the programming discipline used. Finally, simulation results are presented to measure the efficiency of the proposed cross-layer framework.
Wireless Mobile Communication System- Overview
- System Architecture
- Wireless Channel Architecture
- Mobile Radio Channels
- Markov Model for Wireless channel
- Two-state Markov model
- Gilbert-Elliott’s Model
- QoS Scheduling Disciplines
- Fair Queueing
- BER Scheduling: WISPER
- Multiuser Diversity Gain: The Proportional Fair Scheduler
- Provisioning QoS: Throughput and Delay Guarantees
Therefore, the function of the scheduler in wireless networks is not only the allocation of resources (such as time slots) as in cable networks, but also the allocation of powers, data rates, channels or a combination of them when packets are transmitted [12]. The packet scheduling algorithm is one of the most important components of the QoS provisioning mechanism [25], [26].
WCDMA System Model
- Introduction
- Characteristics of WCDMA
- WCDMA Operation Modes
- WCDMA Spreading Operation
- WCDMA Coding and Modulation
- OVSF Channelization Codes
- WCDMA Protocol Layers
- WCDMA Transport Channels
- Dedicated Transport Channel (DCH)
- Downlink Shared Channel (DSCH)
- Frame Structure of Transport Channels
- WCDMA QoS
- QoS Classes
- Technical QoS Categories
- HSDPA-WCDMA Evolution
Both spreading operations are applied to the so-called in-phase (I) and quadrature phase (Q) branches of the data signal. The final bandwidth of the signal at antenna BW will depend on the chip speed W and the modulation scheme.
Cross Layer Scheduling Framework for Supporting Bursty Data Applications in
Introduction
For example, at the physical layer, QoS is synonymous with the acceptable bit error rate (BER) or the signal-to-interference ratio (SIR), while at the Medium Access Control (MAC) layer QoS is usually defined in terms of minimum rate. or maximum delay guarantees. In this chapter, we introduce a cross-layer framework that aims to make the package scheduling procedure more efficient. Using a Finite State Markov Chain (FSMC) model, this framework makes it possible to predict the future state of the wireless channel for each connection.
The traffic scheduler that we propose is adapted to the cross-layer framework and leads to further improvement of system performance. The principles of the proposed framework can be applied to any wireless network that supports multirate services and QoS differentiation between connections.
System Model
- System Model Description
- Signal-to-Interference- Ratio
The total capacity of the OVSF code tree at the BS is divided among the users in the cell. The BS provides the required data rate for each user in the entire downlink shared channel (DSCH). The BS simultaneously serves, Muusers, each of which has a queue (Q) to receive its incoming packets at a data rate, r in each frame, the scheduler allocates resources once in each frame interval, Ts.
The total transmission power available to the BS is shared among the active users in the cell. The BS models each user's wireless channel using a finite state Markov chain (FSMC).
Related Work
The disadvantage of this scheme is that the control parameters used in the priority calculation are predetermined for each traffic class. However, within each traffic class, services do not have exactly the same characteristics and QoS requirements (eg web browsing and networked computer games in the interactive class).
The Cross-Layer Framework
- The Prediction Criterion
The FSMC model, shown in Figure 4.3, represents the time-varying behavior of the Rayleigh fading channel. The choice of SIR thresholds is flexible and the classification can be done in many ways. We chose this method to determine the number of SIR thresholds, which is computationally simple and reasonably accurate for our simulation model.
Then from the Markov channel model (transition and steady state probabilities), the channel state during the transmission of the next frame is predicted and sent to the scheduler in order to prioritize users based on their channel state. Therefore, the prediction procedure is quite simple and is based on the previous channel state information, namely the state k where the channel was found, and the Markov transition probabilities of the FSMC channel model.
The Traffic Scheduler
- The Delay Fair Scheduler (DFS)
- The Delay Fair Scheduler with prediction
Thus, DFS_PRED is able to meet the variable capacity of the wireless interface better than DFS. Pi is used as a criterion to determine whether one connection's service should have priority over another. In the second step, based on the OVSF channelization codes, DFS_PRED allocates the available bandwidth to the connections in the sorted list starting from the higher priority connections.
When all links in the list are capable of transmitting all their respective queued packets during the next frame or.
Numerical Results and Discussion
- Simulation Model
- Bursty Traffic Model
- The Efficiency of the Cross Layer Framework
- Performance Evaluation of DFS_PRED
- Performance Evaluation of Wireless Scheduling Characteristics
As shown in Figure 4.5, DFS_CL outperforms DFS in terms of average packet delay under all traffic loads. Figure 4.6 shows the average queue lengths for the DFS_CL and DFS schemes. Finally, the effectiveness of the framework can also be verified in Figure 4.7, where the bandwidth usage for the DFS_CL and DFS schemes, respectively, is shown.
In this simulation scenario, we evaluate the performance of DFS and DFS_PRED under the cross-layer framework. Therefore, in what follows, we will refer to the two schemes as DFS_CL and DFS_PRED_CL, respectively.
Concluding Remarks
The simulation results demonstrate the efficiency of the proposed scheme in terms of average packet delay, average queue length and bandwidth usage. We also measure key issues for wireless scheduling algorithms, such as fairness and QoS differentiation. Our results indicate that, in terms of both bandwidth usage and average packet delay, significant improvement is possible for any wireless network deploying the proposed cross-layer framework.
Such a technique of the cross-layer framework is considered as a first step in the WCDMA system towards deploying cross-layer design in the future mobile wireless networks. Finally, in our results, we showed that the key issues of wireless scheduling strategies, such as fairness and QoS differentiation, could have no effect by deploying the proposed cross-layer framework.
Radio Resource Management for Handover Provisioning in 3G WCDMA Networks51
Handover procedures in 3G WCDMA Networks
Chat applications use dedicated channels where soft handover is possible, while streaming interactive and background services use the shared channel where only hard handover is possible. Hard handover is the handover procedure in which all the old radio links of a mobile are released before the new radio links are established. Therefore, a hard handover error will result in a temporary connection failure and additional delay caused in the packets waiting to be transmitted in the new cell.
A simplified scenario of soft and hard handover procedures in 3G WCDMA networks is shown in Figure 5.1. In the following sections, we propose a guard code scheme that favors the hard handover calls supported by the DSCH channels.
Part I: A Guard Code Scheme for Handover Traffic Management in WCDMA Systems
- Basic Concepts
- Analysis of OVSF Codes
- Code Blocking and Capacity Blocking
- System Model
- Related Work
- The Guard Code Reservation Scheme
For example, as we mentioned earlier, the available capacity of the OVSF code tree in Figure 5.2 is 5R. Therefore, any monitoring system proposed for 3G systems must be aware of the characteristics of the OVSF code tree. The code occupancy of the OVSF code tree can be modeled by a Markov chain with multiple transitions between the feasible states.
The performance of the proposed guard code reservation scheme is evaluated on an OVSF code tree with capacity totalCT =16. We repeat this scenario to investigate the effect of HO traffic load on the cell.
Part 2: Effective Combination of CAC Scheme and Traffic Scheduling Algorithm for
- System Model
- Admission Control and Bandwidth Reservation
- Traffic Delay Driven Scheduler (DDS) Algorithm
- Related Work
- Numerical Results and Discussion
The reservation threshold is calculated based on measurements of the handover traffic load at the physical layer and adapted to the characteristics of the OVSF code tree. Thus, the reservation factor is used to tune the performance of the proposed CAC. Finally, the reserved capacity in the OVSF code tree must be a multiple of the lowest available rate, R.
As a result, using the proposed CAC improves the HO error rate due to lack of capacity compared to the new call blocking rate. In the first scenario, we want to study the performance of the proposed CAC under different booking factors.
Concluding Remarks
In Part 2, a new design is proposed for effective combination between a CAC mechanism and a scheduling procedure at the MAC layer of WCDMA 3G networks. We introduced a call-level CAC scheme, which is based on a guard code reservation in the OVSF code tree. Code reservation threshold calculation and matching with OVSF codes are encouraged.
The scheduling procedure is not only based on the delay sensitivity, but also based on the predicted error probability of each user in the cell. However, when the total available capacity is shared among the users, the performance evaluation of the scheduler is evaluated in terms of the average packet delay, average queue size and the code utilization.
Minimizing CQI Signaling Overhead in HSPA
- Introduction
- HSDPA System Architecture
- System Concepts and Problem Statement
- System Concepts
- Problem Statement
- Uplink interference analysis
- Prediction-based CQI Reporting Scheme
- SINR respective to CQI value
- Defining the FSMC model of the wireless channel conditions
- Prediction of the next CQI
- Node B Packet Scheduling
- Priority sorting
- Rate allocation
- Performance Evaluation
- Simulation Model
- Effect of the reporting scheme in AMC
- Concluding Remarks
Consequently, we can predict the next CQI on node B, reducing the number of CQI reports needed. The macro cell propagation model proposed in [64] is used to calculate the path loss at distance di (km) from node B. The wireless channel modeling is performed through a four-state FSMC. On the other hand, the performance of P-CQI is close to the optimal performance of the Periodic-CQI_2ms under all traffic loads.
Therefore, P-CQI can achieve performance comparable to the performance of the optimal Periodic-CQI_2ms, while the interference is as low as the Periodic-CQI_4ms. Our results showed that the P-CQI scheme achieves performance comparable to the performance of the optimal Periodic-CQI_2ms, while the interference is as low as the Periodic-CQI_4ms.
Conclusions and Future Research
Conclusions
The performance evaluation of the proposed scheme is evaluated using different code thresholds reservation, different traffic patterns and different HE traffic loads. The calculation of the code reservation threshold and adaptation to the OVSF codes is given. We also investigated the performance of the CAC scheme at different code reservation thresholds.
However, when the total available capacity is shared among the users, the performance evaluation of the. As our results indicated, the main advantage of the proposed scheme is the improvement of the uplink reception quality and at the same time achieves a comparable performance compared to the optimum periodic CQI reporting scheme.
Future work
- More and More Cross-Layer Techniques
The development of next-generation cellular systems (eg, fourth-generation (4G) cellular cellular systems, IEEE 802.11n, etc.) aims to provide high data rates above 1 Gbps. The reason for this is simply the limited knowledge of the future environment in which 4G is supposed to be implemented. The PHY layer of the standard is designed so that different burst profiles and adaptive modulation and coding (AMC) are supported based on channel conditions.
Since there is also the possibility that the wireless channel degrades or becomes unavailable for a certain period of time, the scheduling algorithm at the MAC layer, which is left undefined in the standard, must be aware of the channel state, so that only a connection with a good channel state is scheduled for transmission to achieve multi-user diversity gain. In the near future, the next generation wireless network will be an effective combination of the mobile WiMAX system together with the 4G mobile networks.
Generation Function of the Number of States
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Mark, “Dynamic Fair Scheduling with QoS Constraints in Multimedia Broadband CDMA Cellular Networks,” IEEE Transactions on Wireless Communications, Vol. Cheng, “A Dynamic Multiple-Threshold Bandwidth Reservation (DMTBR) Scheme for QoS Provisioning in Multimedia Wireless Networks,” IEEE Trans.
