Antecedentes

Cross-layer design for achieving the desired performance in wireless networks is not a new area of research and started when wireless communication became more and more attractive to implement especially in remote areas where fixed-line communication was expensive to deploy. Although it may appear that the concept itself is violating the philosophy around the layering concept in networking, the complex issues related to wireless environments such as time-varying channels and propagation loss, suggests the need for cross-layer design to be considered.

Most of the cross-layer designs for radio resource management as in [48 - 49] involve the interactions between the MAC layer and the PHY layer, wherein the MAC layer, proper scheduling techniques are carried out based on specific QoS requirements for each user or data bearer depending on the channel state information feedback from the PHY layer. One interesting technique is shown in [50] where the cross-layer optimisation technique does not require CQI information to be fed back from the user’s side. The real-time video packet transmission is undertaken by adapting the sent bit rate automatically, according to the estimated packet loss due to the expiration of the packet delay deadline based on queuing analysis by considering both the packets queuing delay and transmission delay. Ironically, this technique has somewhat deviated from the 3GPP standards which require the eNodeB to monitor the channel condition of each user continually.

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the performance of their system due to the ever-growing demand for data services, especially for video-related applications by users which have led to a higher volume of traffic at the eNodeB. Consequently, some of the initiatives that have been adopted include the APP layer as part of CLO techniques for radio resource decision making in LTE networks. With this type of cross-layer design architecture, the LTE/LTE-Advanced can achieve multitude objectives towards improving spectrum efficiency, multi-layer diversity gain, adapting to wireless channels and satisfying users within different traffic classes [13]. Most of the APP and MAC/PHY cross-layer architectures are targeted towards data-hungry services such as video streaming applications where high-quality video frames are adjusted and scheduled efficiently to a particular user or users while considering the channel state information for each user as demonstrated by [51 - 54]. In their methods, the video frames or the video encoding parameters are dynamically adjusted to suit the channel conditions for all users by employing the appropriate scheduling methods. However, the study on the performance parameters, such as system throughput, packet loss ratio and delay in a particular time for high delay non-tolerant services, such as video streaming applications, is not stated in those papers. This study is, therefore, considered to be important for network providers if those strict QoS requirements can be achieved for each real-time user.

In some research, the design of the cross-layer optimiser has grown even more complicated when more than two layers (i.e., PHY, MAC and APP layers) need to communicate with the cross-layer optimiser before decisive action can be taken. This means that more information is required to be relayed to the CLO including the channel status from the PHY layer, the queue status from the MAC layer and video content information from the APP layer. For example, the authors in [24] developed a 3-step approach in their video packets multi-user transmission involving all three layers. In the initial step, the video packets from the required

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video streams are arranged based on their importance to the reconstructed quality and assigned with different priorities during transmission. Next, all available subchannels are allocated to each user equitably, according to the size of their chosen packet on the condition that the transmit power is equally distributed across all subchannels. Depending on the subchannel allocation outcome, a modified water-filling power distribution algorithm is applied to distribute the transmit power across the subchannels assigned to each MU. In [25], a different approach is adopted even though the cross-layer architecture still involves the APP, MAC and PHY layers. Besides adapting the source rate based on channel statistics in the APP layer, the authors have introduced a QoS-to-QoE mapping technique to adaptively estimate the visible loss of each video layer over time using ACK history. Alongside the channel state information, the QoS-to- QoE mapping technique has been used to select the suitable MCS in its link adaptation operation. Naturally, a slight violation of the 3GPP standard [21] is observed as the link adaptation is implemented primarily due to the channel condition in each user. In some instances, although the specifications established by 3GPP are met, the issues of MAC complexity and its practical implementation are considered as concerns, as proposed by [26]. This is when the genetic algorithm (GA)-based scheduler implemented together with the cross- layer optimiser, is applied to solve complex optimisation problems.

In previous papers, most cross-layer designs are focused on downlink transmissions. Recently, cross-layer optimisation for m-Health has been proposed by [27] to provide real-time emergency support for mobile patients using SVC multi-video transmission over LTE TDD- SC-FDMA uplink in a single cell. The cross-layer design strategy is to dynamically adjust the overall transmitted multi-video throughput to meet the available bandwidth without compromising the high-quality provision of diagnostic video sequences as compared to less critical ambient videos. Even so, it is the MAC scheduler in the eNodeB that determines the

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suitable rates for the users in the cell to transmit which means; the UEs have no ability to make their own decisions.

Finally, cross-layer optimiser performance resulting from user mobility in the high- speed vehicular environment, such as in a high-speed train and the live transmission of flight recorder data, has been carried out by [75]. The study is carried out by implementing TCP and UDP based throughput measurements on an LTE base station emulator and a mobile radio channel emulator which includes SNR variations as well as user velocity emulation. Even though the study shows that LTE, with the cross-layer implementation, can provide reliable communication links in both high-speed scenarios, further study on normal vehicular and pedestrian scenarios is desirable to study the impact of cross-layer design on their performances.