1. Kuang-Hao Liu et al Presented by Xin Che 11/18/09

2.  IEEE 802.15.3 ◦ For WPANs ◦ Piconet Controller ◦ Peer-to-Peer mode ◦ It is proposed for narrowband wireless communications ◦ It is not suitable for UWB  Concurrent transmissions: Multiple user interference  Ranging capability

3.  UWB-based WPANs formulate the optimal scheduling problem as a utility maximization problem !

4.  Pro: ◦ A utility-based scheduling algorithm aiming at multiclass QoS provisioning with fairness consideration  Cons: ◦ an efficient scheduling algorithm requires feedback information from the network to appropriately make scheduling decisions ◦ it is very difficult, if not impossible, for the PNC to acquire instantaneous channel information of each flow.(Due to peer-to-peer communications)

5.  To estimate the achievable data rate of a flow ◦ PNC can make use of the ranging capability featured by UWB communications [14], [15]. ◦ But, distance information obtained may be noisy due to multipath fading ! ◦ the utility estimation may be biased, and thus affects the scheduling decisions !

6.  Solution in this paper ◦ resort to metaheuristic methods and choose to use the global search algorithm (GSA) [17].  its convergence to the global optimum can be proved,  the tradeoff between computational complexity and efficiency is tunable.  the exclusive-region-based GSA (ER-GSA)  a desired convergence with reasonable computational complexity for practical implementations

7.  Contributions of this paper  The scheduling algorithm for concurrent UWB transmissions maximizes the weighted utility is formulated (NP-Hard)  a utility-based scheduling scheme is proposed to support multiclass traffic with fairness constraint  The assumption of perfect distance information for measuring flow throughput is relaxed by factoring estimation errors into the objective function.  The stochastic optimization problem is solved by the proposed ER-GSA, and its convergence property and computational complexity are studied

8.  Network Structure

10.  Simplified channel model ◦ Assume that a UWB receiver can adapt its transmission rate to an arbitrary SINR level ◦ the achievable data rate r_i of flow i is upper bounded by ◦ neglect the multipath fast fading when we estimate the average data rate ri

11.  Utility Function ◦ Utility is defined as the satisfaction level of a user with respect to the amount of allocated bandwidth.  For heterogeneous traffic, general nondecreasing functions with values within [0, 1]  Traffic types are classified into three classes

12.  Class 1  constant bit-rate app. E.g. audio streams  Class 2  Can adapt to the allocated bandwidth to a certain extent : video stream

13.  Class 3  Can adapt to the allocated bandwidth to a certain extent : video stream

20.  Deriving ◦ very difficult, if not impossible, as U(k) is combinatiorial : dependent on the element in κ.  Use discrete approximation ◦ Let be

21.  ER-GSA ◦ the optimal flow set κ* can be found by evaluating the utility value for each member in K to locate the maximal member  Simple, but has exponential complexity.  Cannot deal with estimation errors. ◦ the GSA is selected as the base to solve (13) since its convergence to a global optimum can be theoretically proved under certain conditions.

22.  GSA ◦ relies on a random sequence generated during the algorithm iterations to efficiently find the optimum. ◦ The resulting random sequence is a Markov chain, where each state represents a point in the solution space that has been visited by the algorithm ◦ In each iteration, the transition of the Markov chain is determined by comparing the objective value of the current state and that of a randomly chosen point from the solution space

25.  The convergence of ER-GSA

28.  Utility Update

29.  The scheduling policy has the followoing properties :

30.  Experiment Setting

31. ◦ Each superframe contains ten slots. ◦ The size of exclusive region, which is denoted as dER, is set to 2 m, ◦ in Section V-C, we vary the size of exclusive region to study its impact on the aforementioned three performance metrics.

32.  Traffic

33.  Utility-Based Scheduling

35.  Utility Vs. Fariness ◦ Total Utility Vs. Fairness

36.  Utility Vs. Fariness

37.  Minimum Utility

38.  Algorithm Efficiency and Stability

40. ◦ Stability factor

41.  Stability

42.  a utility-based optimal scheduling for concurrent UWB transmissions supporting heterogeneous traffic has been proposed  it is found that the size of the exclusive region in UWB networks is independent of the transceiver distance, which, on the contrary, is a dependent parameter in narrowband wireless systems.  The proposed algorithm can also maintain a good balance between the computation complexity and the robustness against measurement and estimation errors, and thus, it suits UWB network schedulers with limited computation power.