MIMO Systems for ensuring Multimedia QOS over Scarce Resource Wireless Networks Saket Gupta
Sparsh Mittal
Sudeb Dasgupta
Ankush Mittal
Student Electronics and Computers, IIT Roorkee +91 9411500855
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Student Electronics and Computers, IIT Roorkee +91 9410371754
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Assistant Professor Electronics and Computers, IIT Roorkee +91 1332-285666
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Associate Professor Electronics and Computers, IIT Roorkee +91 1332-285713
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ABSTRACT While much research has been done on multimedia compression and network resource optimization, multimedia delivery over wireless still entails the need for efficient network adaptive transmission and reception system. MIMO (Multiple input multiple output) systems offer parallel sub-channel transmission with tremendous increase in reliability and data rates over unreliable wireless channels. In this paper, we present algorithmic implementation of video streaming for preferential adaptation of CEZW+ (Color Embedded Zero Wavelet) compressed videos over wireless, in the facade of variable network bandwidth. Educational videos, involving video streaming of classroom videos are segmented into component blocks. Based on their relative importance and motion, segments with higher relevance are allocated more bandwidth. Moreover, transmission of more important data by higher quality sub-channels by unequal power distribution in antennas improves efficiency. Different video segments are simultaneously transmitted from different transmit antennas, boosting data rates and reliability. Our results prove excellent enhancement in streaming reliability and data rates.
limit and reducing transmission storage cost, channel BW and storage capabilities are limited and relatively expensive in comparison with the volume of these raw digital signals. Such is required in E-learning multimedia services, which mostly include transmission and streaming of e-learning videos. Many institutes, like MIT (USA) and IITs (India), have opened web servers for free lecture-on-demand on several courses [1-4]. Remote laboratories also demand real-time multimedia content delivery [5-7]. However, a serious blockage towards multimedia e-learning is the non-availability of required bandwidth to view the lecture videos at good resolution because of their large size. [8] shows CEZW+ compression of video with approach of segmenting video and separately encoding each segment. Our system achieves highly improved performance over that system by use of MIMO framework, reaching efficient tradeoff between constraints of multimedia transmission - maximum transmission rate and network performance, by allocating bandwidth to different visual objects of video using UPA MIMO systems.
Categories and Subject Descriptors H.4.3 [Communications Applications]: Computer conferencing, teleconferencing, and videoconferencing – video streaming; I.4.6 [Segmentation]: Edge and feature detection, Region growing and partitioning – video segmentation; C.2.1 [Network Architecture and Design]: Wireless communication; E.4 [Coding and Information Theory]: Formal models of communications.
General Terms Algorithms, Performance, Design, Reliability.
Keywords MIMO Streaming, segmentation, CEZW+ compression, Alamouti STBC, power-bandwidth allocator, synchronization PDU.
1. INTRODUCTION With continuous progress in technology and pushing up of BW Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. ICAC Conference’08, February 21–22, 2008, Chikhli, M.S.INDIA, Country. Copyright 2004 ACM 1-58113-000-0/00/0004…$5.00.
Figure 1 : Snapshots of classroom Lecture sessions Foschini and Gans [9], Foschini [10] and Telatar have shown that channel capacity for MIMO system is increased as number of antennas is increased, proportional to the minimum number of transmit and receive antennas. Large proportion of research related to image/video communication has focused on distribution of available resources; transmission power between different parts of the source is optimized in such a way that the distortion is minimized at the receiver [11, 12, and 13]. For videos coded using most of the current standards, different parts of the bitstream have different importance. Therefore, distortion can be reduced if more important parts of these sources are transmitted with higher reliability at the expense of lesser reliability for less important parts. This trade-off is achieved in our system by designing Spatial Multiplexing [14] and Alamouti [15] STBC codes.
2. SYSTEM IMPLEMENTATION 2.1 Segmentation Different segments of lecture videos are extracted from the video. Each of the segments so divided are separately coded using CEZW+. These are transmitted through different antennas with Unequal Power Allocation (UPA), based on relative importance and quality of the video segment streams. Lectures are segmented based on edge detection, subtraction and dilation and then compressed.
Rayleigh flat fading frequency independent channel configuration.
Teacher Blackboard
Background
Figure 2. Video Segmentation of the classroom lecture video
2.2 MIMO system for preferential streaming DDM decides how much power should be allocated to different streams, depending upon perceptual quality of video and bandwidth available. Alamouti STBC with 3 sets of 2 antennas, for each transmission segment is employed; SM by separate segments directed to separate antenna sets. SPATIAL E-Learning Video
MULTIPLEXING and STBC Combined coding
A N T E N N A
DYNAMIC DECISION MAKER ( DDM)
UNEQUAL ALLOCATION OF MIMO ANTENNA GAINS TO DIFFERENT VIDEO SEGMENTS
DYNAMIC BANDWIDTH ALLOCATION TO DIFFERENT SEGMENTS
A N T E N N A
SEGMENT A
MIMO OFDM TRANSMISSION OF DIFFERENT SEGMENTS
SEGMENT B
A N T E N N A
Segmentation and CEZW Compression Module
SEGMENT C
Figure 3. MIMO transmitter with UPA and BW allocation Bandwidth allocator decides BW for each segment based on video PSNR and its relative importance and perceptual quality. More details can be found in [8]. However, the retransmission of consecutive unchanged segment frames, in contrast to the above method. This is done using a special bit in MAC PDU sent. Frame synchronization at the MMSE receiver is achieved through putting timestamps (i.e. the sequencing in the original video) for each frame in the MAC PDU. Unequal Power is allocated using different M-ary QAM modulation for different segments depending upon PSNR; higher M for higher power requirement.
3. RESULTS Reliability increase using multiple modulations is depicted by the reduction in Bit Error Probability by UPA as calculated by [16]: k 1/2 3log L 2 E 2(1 L1 ) Pb Q[ ( 2 2 ) b ] ; M = 2 , L = (M) , k is log 2 L L 1 NO even, and Q(x) is a complementary error function, Eb/N0 is Eb calculated using where k is sps. PSNR[dB] =
N0
[dB]+101og(k)
Table 1. Unequal Power Allocation scheme PSNR value (dB)
Resultant Bit Error Prob. 4 QAM 16 QAM 64 QAM 10-30 0.48E-12 0.00129 0.16061 30-40 3.1E-14 4.532E-09 0.00103 40-50 ~0 1.264E-12 4.875E-05 50-55 ~0 3E-15 5.118E-06 Increase in data rates are measured by a single channel; multiple I/P single O/P; single I/P multiple O/P; multiple I/P multiple O/P
Figure 4. Data rate enhancement with increase in antennas
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