Violencia

Manhattan Model is proposed in [83] for broadband systems. The Manhattan model is an attractive scenario for deployment of the CoMP in a dense urban environment, where fiber has already been deployed and can be reused to transport the radio signals to/from the RRHs, or can be economically deployed. Furthermore, end users will be mainly in line-of-sight conditions or near line-of-sight with the antenna. This Manhattan deployment consists of a rectangular regular grid of RRHs. This rectangular grid follows the regular street structure of a city with buildings, streets, and blocks of the same size. The RRHs are considered to be deployed at optimal positions on the streets.

For purposes of the CoMP system, the CoMP area is defined as the group of RRHs that are jointly processed at the CU. Within this CoMP area, a user can be attached to only one of the RRHs using selective antenna algorithms, or to more than one of the antennas using MIMO and other spatial diversity schemes. For example, a Manhattan deployment configuration with 4 RRHs or nodes per processing area and frequency reuse factor 1. The RRHs are considered to be located at the main street-crossing with four RRHs in a cell. The side-length of a building block (b) and the street width (s) are set to be b=200 meters and s=50 meters, respectively. So, the CoMP-cell covers 16 building blocks and cell coverage is about 1000×1000 square meters.

The propagation model proposed in [94] is considered, where the path-loss, shadow and multipath models for the urban micro-cell environment (Manhattan B1 model) are adopted.

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5.3. 3D Video Transmission and User Resource Allocation Algorithm

In this section the definition of the necessary cross-layer information exchanged through a signaling mechanism among the components of the considered system architecture is presented. Multimedia based services is having an important impact in the 4G and beyond networks, where 3D applications are emerging. 3D video transmission for the LTE network is analyzed in [95], and general QoE on 3D streaming is evaluated in [96]. However due to interferences, cell edge users still suffer from bandwidth and spectral efficiency limitations when compared with users closer to cell site. In this chapter the CoMP is used in order to improve capacity for quality sensitive applications, such as 3D video, where particular features are analyzed.

Figure 5.2: Cross-Layer Block Diagram [97].

PHY (RB Allocatio n

U

SW

SRI

Cross-Layer Optimizer (CLO)

Transmitter Channel M A C Sch ed ul er IP Flow 1 IP Flow 2 IP Flow n UE 1 UE 2 UE k MCS Controller Resource Allocation U CX RA X SR I M SI, CS I M CX

Playout Time (PTI)

data flow control path

APP Layer MAC Layer PHY/LLC Layer Users

Access Point (AP) User Equip. (UE)

PER PDV THI CCI SSI MIH-Like Information Service (IS)

*Eac h UE dem and s up to l IP Flows (SVC vi deo traffic)

SS X Application Server Video App SFX CQ I VVN VLN CES UEP Controller V IR TUAL QUEUES

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The cross-layer architecture which is described in this section, is a result of collaborative work in the scope of the ROMEO project with University of Patras [97]. The architecture is presented in Figure 5.2, including the control signals for cross-layer communication. Multiple colors indicate the dependence of control information, coming out of the Cross-Layer Optimizer (CLO).

In fact, the objective is to combine the informations of the upper layer video application with the CoMP (suitable antenna/radio head and frequency resources) to maintain the QoS of the 3D video during the scheduling period.

5.3.1.1 3D Video Transmission

The video content generated in the application layer (APP) Layer by the 3D video application can be encoded using two different approaches. In the first approach each View ( e.g. Base and Non-Base View in the case of a stereoscopic 3D video) can be encoded independently using Scalable Video Coding (SVC) encoding. Scalable video coding (SVC) [98] [99] decomposes the video stream into multiple video layers which are classified as base layer (BL), that provides a basic video quality and can be decoded alone without the need of delivering and decoding the rest of the video layers, and enhancement layer(s) (EL), that are additional video layers which help to gradually increase the quality of the decoded representation of the video. Scalability is very useful for service continuity under bandwidth varying networks by adapting the quality of the streamed video without the need of re-encoding the video source. In the case of multi-view video applications the total data rate per user is considered to be equal to the sum of the bit rate of each layer (BL+EL1+EL2…) multiplied by the number of views V, e.g. V=2V = 2 for stereoscopic 3D video.

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A second approach - Multiple Description Coding (MDC) video coding - is also considered. This approach aims primarily at error resiliency rather than the SVC’s stream adaptability. MDC technique fragments a single media stream and creates several independent sub-streams that are referred to as Descriptions. Descriptions contribute to one or more characteristics of the reconstructed video, such as temporal or spatial resolution frequency content or PSNR (Peak Signal-to-Noise Ratio). The advantage of MDC is that all Descriptions are self-contained and can be decoded without the need of decoding other Descriptions, unlike SVC. In order to decode the media stream, any Description can be used; however, the quality improves with the number of Descriptions received in parallel. Since there is no priority between each Description, an arbitrary subset of Descriptions can be decoded, thus achieving bit rate adaptation but also consolidating error-resilience over unreliable channels with unavoidable packet loss and congestion. Accordingly, for MDC video coding, the selected Views can be encoded using two different Descriptions, namely MDC1 and MDC2 that represent even and odd information lines, respectively for the Color and Depth channels. A layer coding mechanism like SVC can be used after data partitioning, to generate a BL and ELs for the descriptions, e.g. MDC1B, MDC1E and MDC2B, MDC2E.

UEP controller is a mechanism that enables Unequal Error Protection (UEP) scheme for the transmission of the video content. UEP processing can lead to better performance for the perceived video quality in erroneous environments, by protecting in a different manner, parts of video data that have different level of importance, without increasing the size of the overall data. A coding scheme that uses UEP means that parts of the bit-stream that are more susceptible to errors causing disturbances

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are provided with more protection (i.e. a lower code rate) and vice versa. UEP methods are usually combined with FEC techniques. Using UEP techniques and prioritization of layers, the layered structure of a scalable video stream and different priorities among the layers could be supported for the cross-layer design.