An Adaptive Control for Video Transmission Over Bluetooth

Transcription

1 An Adaptive Control for Video Transmission Over Bluetooth Hassan B. Kazemian, Senior Member, IEEE, and Li Meng SILFIA RIFKA

2 This paper is concerned with : Transmission of a moving picture expert group (MPEG) video stream over a Bluetooth channel, using an adaptive neuro-fuzzy technique.

3 Problems MPEG variable bit rate (VBR) video sources over a network have long delay and unacceptable data loss, due to high variations in bit rate. Transmission rate could be unpredictable in a Bluetooth network due to interferences by other wireless devices or general Bluetooth channel noises. Subsequently, it is almost impossible to transmit VBR data sources over Bluetooth without excessive delay or data loss.

4 Problem s Solving The computer simulation results show that the use of the neuro-fuzzy controller reduces excessive delay and data loss at the host-controllerinterface, as compared with a conventional VBR video transmission and a rule-based fuzzy controller (RBF1) in Bluetooth.

5 Introduction(1) Moving Picture Expert Group (MPEG) Variable Bit Rate (VBR) encoding scheme is a preferred compression technique for transmissional purposes as it produces a constant image quality. MPEG VBR video sources have high bit rates and require a large bandwidth for the transmission over a network.

6 Introduction (2) This paper takes the video transmission research over Bluetooth further by using a novel adaptive neuro-fuzzy (NF) technique. The proposed control system comprises of two controllers. 1. A rule-based fuzzy (RBF) scheme 2. Adaptive NF scheme

7 Introduction (3) RBF scheme, controls the output rate from the MPEG encoder and the arrival rate at the traffic-shaper, in order to prevent either saturation or starvation of the buffer. An adaptive NF scheme, which monitors and reduces the burstiness of the departure rate from the traffic-shaper to facilitate the smooth transmission of MPEG VBR video sources over Bluetooth.

8 Bluetooth Channel (1) Bluetooth provides two types of links: 1. Synchronous Connection Oriented (SCO) link. The SCO link is mainly used to carry audio and video real-time traffic. 2. Asynchronous Connection-Less (ACL) link. The ACL link is typically suitable to support data applications.

9 Bluetooth Channel (2) The Bluetooth specification provides flow control for the HCI, so that data transport across the HCI slows down when the HC buffer is overloaded, while runs at full speed the rest of time. The host can only send data when there is space available in the HC buffer.

10 Parameters Of The RBF And NF Controllers (1)

11 Parameters Of The RBF And NF Controllers (2) 1. Traffic-shaping buffer is introduced to manipulate and coordinate the VBR encoding video prior entering the Bluetooth channel. The shaper buffer s role is to smooth the video output traffic and to partially eliminate the burstiness of the video stream entering the Bluetooth network. 2. The inputs to the RBF controller are the fuzzified mean value X(k) and the fuzzified standard deviation σ(k) of the queue length from the traffic-shaping buffer. 3. The output from the RBF controller is the fuzzified time-interval of arrival data

12 Parameters Of The RBF And NF Controllers (4) 4. The inputs to the NF controller are the fuzzified queue length X(f) from the traffic-shaping buffer and the fuzzified available tokens from the generic cell rate algorithm commonly known as the leaky-bucket Y(f) 5.The output from the NF controller is the fuzzified departure data rate rd(f), f is denoted for a frame.

13 Parameters Of The RBF And NF Controllers (1)

14 Parameters Of The RBF And NF Controllers (5) MPEG uses intra-frame compression to remove redundancy within frames and inter-frame compression to take advantage of the redundancy contained over sequences of many pictures. This creates Long Groups of Pictures (GOPs) Based on phase alternate line (PAL), in the computer simulation it is assumed that there are 24 frames in one second and a GOP contains 12 frames; therefore there are two GOP s in one second.

15 Parameters Of The RBF And NF Controllers (6) 6.The (k+1)th GOP is the group which is in the process of passing through the model to reach the token-bucket and eventually entering the Bluetooth channel. 7. The (k+2)th GOP is the group presently being encoded by the MPEG encoder. When the arrival rate is greater than the departure rate, data would be held in reserve in the token-bucket; and when the memory space in the token-bucket is full, data would be dropped. 8. The range of the departure rate Rd(f) is between the arrival rate Ra(k+1) and the actual token (transmission) rate ractual 9. The arrival rate Ra(k+1) is controlled on a GOP by GOP basis and the departure rate Rd(f) is controlled on a frame by frame basis.

16 Parameters Of The RBF And NF Controllers (1)

17 Parameters Of The RBF And NF Controllers (7) In Fig. 1, the block rd to Rd calculates the departure rate Rd(f) from the fuzzified departure rate rd(f) using (1) Where rd(f) is the fuzzified Rd(f) and

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19 Parameters Of The RBF And NF Controllers (8) In Fig. 2, there are two sources of data to be released from the traffic-shaper. One is the compressed video sequence of the MPEG encoder. The other is the data kept in the traffic-shaper. The data currently kept in the traffic-shaper within one GOP period and deliver video sequence without delay. Then the rate that data should be sent is

20 Parameters Of The RBF And NF Controllers (9)

21 Parameters Of The RBF And NF Controllers (8) where x(f) denotes the queue length in the traffic-shaper and TGOP denotes the time period of a GOP. When Rto-send is larger than ractual, some data will be kept in the token bucket. Therefore, the maximum value that Rd could be without causing data loss is Where y(f) is the amount of memory space left in the token bucket and Tframe is the time period of a frame. With Rto-send and Ravailable,

22 An Adaptive NF Scheme (1) An adaptive technique is incorporated into the control scheme through the use of an NF controller. First, a neural network represents an RBF1 controller. Such a network generally has a three-layered architecture and uses fuzzy sets (i.e. fuzzy membership functions) as its weights at the input and output layers. The nodes of the hidden layer represent the fuzzy IF THEN rules. Next, the standard back-propagation procedure for multilayer neural networks is adopted to train the fuzzy membership functions The NF controller is based on the Sugeno or Takagi Sugeno Kang method

23 An Adaptive NF Scheme (2) The general first-order Sugeno fuzzy model has rules of the form : where A and B are the antecedents, while p,q, and r are all constants.

24 An Adaptive NF Scheme(3)

25 An Adaptive NF Scheme(4) Fig.3 : shows the structure of the NF controller. Both input variables Y(f) and X(f) have generalized bell-shaped membership functions. The generalized bell function depends on three parameters a and b (shape of membership function), and c (center of curve) given by:

26 Input-output mapping of the RBF1 controller.

27 An Adaptive NF Scheme(5) A.Training Set In order to provide enough information for training these parameters, the number of input output training pairs must be larger than the number of available parameters. As indicated, each GOP has 12 frames. From sugeno model and bell function the number of free or available parameters for training in the NF controller is where the inputs are X(f) and Y(f) with 3 and 4 membership functions, and the output is Rd with 12 membership functions

28 An Adaptive NF Scheme (6) Therefore, each training loop must at least involve GOPs. In the computer simulations carried out, the parameters of membership functions of NF controller are adjusted once every 10 GOPs. That is to say, the training set for each training procedure contains 120 input output pairs. B. Initial Set Up The RBF1 controller is incorporated in the NF controller. Table I represents the initial 12 rules associated with the RBF1 controller. The output of RBF1 controller is the normalized time interval of departure rate from id the traffic-shaper. The input output mapping of RBF1 controller see table I The proposed NF control scheme has been tested on three real-time video clips. However, due to restriction in the number of pages allowed for publications, only two clips: 007 Die Another Day and The Lord of the Rings The Two Towers are presented in this paper.

29 Computer Simulation Results (2) Table I : Rules Of The RBF1 Controller without the supervision of the NF scheme. Table II : summarizes some basic features of the two resized testing clips Table III : shows the simulated interference noise in each experiment. Non-noise situation is simulated to examine if the maximum bandwidth of Bluetooth ACL is sufficient for the clips when there is no noise present. Table IV : The variance of output rate from the MPEG encoder for the open loop VBR system Table V-VI : percentage of dropped data at the token bucket is substantially lower for the NF controller than for the RBF1 controller, with or without the noise.

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31 Non-noise situation is simulated to examine if the maximum bandwidth of Bluetooth ACL is sufficient for the clips when there is no noise present In the computer simulation, is used as a Gaussian distribution, where,e is the mean value, and v is the standard deviation. The mean value of the Gaussian interference noise is always zero.

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33 In Tables V and VI, the variance of output rate from the traffic-shaper is more consistent for the RBF1 controller than for the NF controller. This is because in the RBF1 scheme, the controller always reduces the variance of output rate from the traffic-shaper irrespective of the noise and the channel condition.

34 CONCLUSION The proposed a NF controller is designed, applied and compared with the open loop VBR encoding system and the RBF1 controller for MPEG VBR video over a Bluetooth ACL link. The computer simulation results demonstrate that the use of the adaptive NF scheme reduces the variance of output bit rate to the Bluetooth network, reduces the number of dropped data, and produces better and stable video image quality, as opposed to the open-loop VBR system and the RBF1 scheme. The reason that the NF controller produces an improved image quality is because, the adaptive NF scheme has a supervisory role to adjust and change the parameters of the membership functions of the rules in the RBF1 controller

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