## 2 Related Studies  
Several techniques have been investigated in the literature to address video quality issues over wireless channels [13; 14; 15; 16; 17; 18; 19; 20; 21; 22]. Generally, QoS or QoE [3] over multimedia communication channels can be categorized according to various metrics including: Bit Error Rate (BER), Packet Loss Ratio (PLR), Blocking Probability (BP), Collision Probability (CP), Dropping Probability (DP), Energy Efficiency (EE), and Spectrum Efficiency (SE). In [23], the authors proposed a utility-based H.264/Scalable Video Coding (SVC) video streaming scheme to improve quality over a multi-channel Cognitive Radio Network. In [24], the authors examined the comparative effects of channel errors on selectively encrypted video bitstreams by two H.264 codec entropy coders Context Adaptive Binary Arithmetic Coding (CABAC) and Context Adaptive Variable Length Coding (CAVLC). They determined the combined effect of compression and encryption on the video quality and concluded that CAVLC is more susceptible to channel error. CABAC is being utilized by all advanced encoders; then, this finding [24] serves as a base to devise an advanced bit-error protection method for CABAC entropy coder of H.264/AVC (as considered in this paper). In [25], an extended Selective Encryption (SE) model for both H.264/AVC and HEVC encoded streams was introduced in which the regular mode of CABAC was used. Motion, texture, and structure encryption was applied to the video frames for the partial protection of video content. The performance of the proposed technique was assessed by taking the relative PSNR and SSIM. The HEVC codec increases the compression efficiency but has less error-resilient features [13] and is more sensitive to channel bit errors because of more encoded redundant content [14]. Thus, HEVC encoded video requires more efficient error concealment techniques. Previously, instead of error concealment, [PERSON] et al. [15] had proposed an error resilience coding scheme for H.264/AVC video coding, in which a group of Macroblock (MBs) are encoded with adaptive intra-refresh. In [16], a hybrid of Block Boundary Matching and Directional Interpolation Error Concealment (DIECA) methods was employed to preserve the quality of 3D H.264/MVC encoded video transmitted over an error-prone wireless communication network. In this work, for the lost frames, a Depth-Assisted Error Concealment (EIDD-DAEC) [17], Bayesian Kalman Filtering for Error Concealment (BKF-EC), depth-assisted motion vectors (MVs), and the disparity vectors (DVs) are exploited to estimate and recover the corrupted colored frames and achieve the better objective and subjective quality. In [18], an effective channel-modeling scheme was implemented using source rate control and adaptive playback techniques. Furthermore, for enhancing perceptual video quality over a Cognitive Radio Network (CRN), the authors formulated a content-aware Channel Quality Index (CQI) metric-based channel allocation scheme [19]. Error bursts frequently occur in wireless channels due to slow or fast fading. They are also potentially more damaging to compressed video streams compared to isolated errors due to the fragile nature of a highly compressed video bitstream. The Gilbert-Elliot(GE) [26; 27] is extensively used to represent 'bursty' error patterns in transmission channels, allowing analysis of the transmission efficiency, such as how many errors an error-recovery scheme detects and corrects induced in its channel. Prior work has also focused on different video error control techniques including source and channel rate control [20], adaptive playback control [18], and error concealment [21; 22]. However, the status of the received signal can only be predetermined from the transmitter signal if an accurate communication channel is modeled [9].