A Cross-Layer Scheduling Algorithm With QoS Support in Wireless Networks Qingwen Liu, Student Member, IEEE Xin Wang, Member, IEEE, Georgios B. Giannakis, Fellow, IEEE IEEE TRANSACTIONS ON VEHICULAR TECHNOLOGY, VOL. 55, NO. 3, MAY 2006 Presented by Jason, Li-Yi Lin 2019/1/15 NTU, IM, OPLab

Outline Introduction System Architecture Scheduler Design Simulations Conclusion and Future Directions 2019/1/15 NTU, IM, OPLab

Introduction Scheduling plays an important role in providing QoS support to multimedia communications in various kinds of wireless networks. However many wireless standards define only QoS architecture and signaling, but do not specify the scheduling algorithm that will ultimately provide QoS support Introduce a priority-based scheduler at the MAC layer for multiple connections with diverse QoS requirements, where each connection employs adaptive modulation and coding (AMC) scheme at the PHY layer. 2019/1/15 NTU, IM, OPLab

Outline Introduction System Architecture Scheduler Design Simulations - A. Network Configuration - B. QoS Architecture at the MAC - C. AMC Design at the PHY Scheduler Design Simulations Conclusion and Future Directions 2019/1/15 NTU, IM, OPLab

System Architecture – Network Configuration (1/6) 2019/1/15 NTU, IM, OPLab

System Architecture – Network Configuration (2/6) All connections communicate with the BS using TDM / TDMA At the PHY, multiple transmission modes are available to each user, with each mode representing a pair of a specific modulation format and a forward error control (FEC) code The AMC selector determines the modulation-coding pair, whose index is sent back to the transmitter through a feedback channel. 2019/1/15 NTU, IM, OPLab

System Architecture – Network Configuration (3/6) BS SS 2019/1/15 NTU, IM, OPLab

System Architecture – Network Configuration (4/6) Transmission modes (TM): 2019/1/15 NTU, IM, OPLab

System Architecture – Network Configuration (5/6) At the MAC, each packet contains a fixed number of bits , which include packet header, payload, and CRC bits. At the PHY, each frame contains a fixed number of symbols , and the frame duration (in seconds) is constant. With TDM, each frame is divided into time slots. Let each time slot contain a fixed number of symbols. The time slots contain control information and pilots; the time slots convey data. 2019/1/15 NTU, IM, OPLab

System Architecture – Network Configuration (6/6) MAC PHY symbols 2019/1/15 NTU, IM, OPLab

System Architecture – QoS Architecture at the MAC (1/2) Unsolicited grant service (UGS) - this service provides guarantees on throughput, latency, and jitter to the necessary levels as TDM services - the QoS metrics are the packet error rate (PER) and the service rate Real-time polling service (rtPS) - provides guarantees on throughput and latency, but with greater tolerance on latency relative to UGS - the QoS metrics are the PER and the maximum delay (or the maximum delay for a given outage probability) 2019/1/15 NTU, IM, OPLab

System Architecture – QoS Architecture at the MAC (2/2) Nonreal-time polling service (nrtPS) - provides guarantees only in terms of throughput - the QoS metrics are the PER and the minimum reserved rate Best effort (BE) service - provides no guarantees on delay or throughput - although no delay and rate is specified for BE connections, a prescribed PER should be maintained over wireless channels 2019/1/15 NTU, IM, OPLab

System Architecture – AMC Design at the PHY (1/3) Efficient bandwidth utilization for a prescribed PER performance at the PHY can be accomplished with AMC schemes Each connection with rtPS, nrtPS, and BE services relies on AMC at the PHY. The objective of AMC is to maximize the data rate by adjusting transmission modes to channel variations while maintaining a prescribed PER 2019/1/15 NTU, IM, OPLab

System Architecture – AMC Design at the PHY (2/3) Let denote the total number of transmission modes available ( for TM) The boundary points are denoted as To avoid deep-channel fades, no data are sent when which corresponds to the mode with rate bits/symbol 2019/1/15 NTU, IM, OPLab

System Architecture – AMC Design at the PHY (3/3) Approximate the PER expression in AWGN channels as Set the region boundary for the transmission mode to be the minimum SNR required to guarantee 2019/1/15 NTU, IM, OPLab

Outline Introduction System Architecture Scheduler Design Simulations Conclusion and Future Directions 2019/1/15 NTU, IM, OPLab

Scheduler Design (1/8) - Scheduling UGS Connections The transmission mode could be selected in the initial service access phase to meet the average PER requirement Then, the transmission mode is fixed during the whole service time Denote the total time slots allocated to UGS connections as per frame. The residual time slots are 2019/1/15 NTU, IM, OPLab

Scheduler Design (2/8) - Scheduling rtPS, nrtPS and BE connections Each connection adopts AMC at the PHY Given a prescribed PER , the SNR thresholds for connection are determined as described above by setting The possible transmission rate (capacity) can be expressed as where 2019/1/15 NTU, IM, OPLab

Scheduler Design (3/8) - Scheduling rtPS, nrtPS and BE connections At the MAC, the scheduler simply allocates all time slots per frame to the connection where is the PRF for connection at time If multiple connections have the same value , the scheduler will randomly select one of them with even opportunity 2019/1/15 NTU, IM, OPLab

Scheduler Design (4/8) - Scheduling rtPS, nrtPS and BE connections The PRF for a rtPS connection at time is defined as where is the rtPS-class coefficient and is the delay satisfaction indicator, which is defined as with denoting the guard time region ahead of the deadline , and denoting the longest packet waiting time 2019/1/15 NTU, IM, OPLab

Scheduler Design (5/8) - Scheduling rtPS, nrtPS and BE connections If , i.e., , the delay requirement is satisfied If , i.e., , the packets of connection should be sent immediately to avoid packet drop due to delay outage 2019/1/15 NTU, IM, OPLab

Scheduler Design (6/8) - Scheduling rtPS, nrtPS and BE connections Guarantee the minimum reserved rate to each nrtPS connection If data of connection are always available in queue, the average transmission rate at time is estimated over a windows size as 2019/1/15 NTU, IM, OPLab

Scheduler Design (7/8) - Scheduling rtPS, nrtPS and BE connections The PRF for an nrtPS connection at time is defined as where is the nrtPS-class coefficient and 2019/1/15 NTU, IM, OPLab

Scheduler Design (8/8) - Scheduling rtPS, nrtPS and BE connections The PRF for a BE connection at time is defined as where is the BE-class coefficient The role of and in (6), (9), and (11), respectively, is to provide different priorities for different QoS classes 2019/1/15 NTU, IM, OPLab

Outline Introduction System Architecture Scheduler Design Simulations Conclusion and Future Directions 2019/1/15 NTU, IM, OPLab

Simulations (1/10) Assumptions: A1: The wireless channel quality of each connection remains constant per frame, but is allowed to vary from frame to frame A2: Perfect channel state information (CSI) is available at the receiver via training-based channel estimation. The corresponding transmission mode selection is fed back to the transmitter without error and latency. A3: Error detection based on CRC is perfect. A4: if a packet is received incorrectly after error detection, we declare packet loss. 2019/1/15 NTU, IM, OPLab

Simulations (2/10) Channel Model: The received SNR per frame is a random variable with a Gamma probability density function, i.e., where , is the Nakagami fading parameter Finite-state Markov chain (FSMC) model 2019/1/15 NTU, IM, OPLab

Simulations (3/10) Parameter Setting: The frame length is ms The packet length at the MAC is fixed to bits For each rtPS connection , we assume that the arrival process to the queue is Bernoulli distributed with a given average rate and parameter The instantaneous arriving rate at time can be expressed as 2019/1/15 NTU, IM, OPLab

Simulations (4/10) rtPS connection 1 rtPS connection 2 2019/1/15 NTU, IM, OPLab

Simulations (5/10) The guard time is set to ms The delay outage probability where window size ms 2019/1/15 NTU, IM, OPLab

Simulations (6/10) For each nrtPS connection , we assume that the data are always available nrtPS connection 3, 4 2019/1/15 NTU, IM, OPLab

Simulations (7/10) For each BE connection , we assume that the data are always available The rate performance of nrtPS and BE connections is also evaluated by the average service rate over a window size ms The system is simulated over 60000 ms with bounds BE connection 5, 6 2019/1/15 NTU, IM, OPLab

Simulations (8/10) 0.77% 0.24% 6.7 4.5 3.1 5.9 Average 2019/1/15 NTU, IM, OPLab

Simulations (9/10) 1.06% 0.29% 5.8 3.4 0.4 1.0 Average 2019/1/15 NTU, IM, OPLab

Simulations (10/10) 0.78% 0.18% 2.5 2.9 Average 2019/1/15 2019/1/15 NTU, IM, OPLab

Outline Introduction System Architecture Scheduler Design Simulations Conclusion and Future Directions 2019/1/15 NTU, IM, OPLab

Conclusion and Future Directions (1/3) Efficient bandwidth utilization is achieved through in Delay bound is provided for rtPS connections and we can control the delay outage probability below the practically acceptable values by adjusting Throughput is guaranteed for nrtPS connections if sufficient bandwidth is provided 2019/1/15 NTU, IM, OPLab

Conclusion and Future Directions (2/3) Implementation complexity is low because the scheduler simply updates the priority of each connection per frame Flexibility is provided because the scheduling does not depend on any traffic or channel model Scalability is achieved. 2019/1/15 NTU, IM, OPLab

Conclusion and Future Directions (3/3) The upper-bound and the delay guard time were set heuristically, their effects on performance are worthy of further research Scheduling multiple connections each time may lead to better performance The fairness issue for the users in the same service class is another topic The effects of imperfect channel state information due to estimation error and feedback latency are also worth further study 2019/1/15 NTU, IM, OPLab

Thanks for your listening 2019/1/15 NTU, IM, OPLab

Conclusion and Future Directions For rtPS For nrtPS For BE 2019/1/15 NTU, IM, OPLab

Finite-state Markov chain (FSMC) model 2019/1/15 NTU, IM, OPLab

Finite-state Markov chain (FSMC) model (cont’) 2019/1/15 NTU, IM, OPLab