<p>Real Time (RT) and Non-Real Time (NRT) multimedia content demand on mobile devices are increasing at a high pace. Long Term Evolution-Advanced (LTE-A) is expected to cater these demands. However, LTE-A operates at fixed spectrum which leads to spectrum scarcity. Cognitive Radio (CR) is one the promising technologies that is used to overcome spectrum scarcity and implementation of CR into LTE-A will improve spectrum availability and efficiency of the network. Furthermore, with addition of Packet Scheduling (PS) in the cognitive LTE-A, QoS requirement of the mobile users can be guaranteed. However, the study on the stated is very limited. Thus, this paper models, simulates and evaluates performance of five well-known PS algorithms for supporting the RT and NRT multimedia contents. The simulation results show that Maximum- Largest Weighted Delay First (M-LWDF) is the best candidate for implementation in the cognitive LTE-A.</p>

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A packet scheduling algorithm known as Enhanced Maximum-Largest Weighted Delay First (EM-LWDF) is proposed in this paper. It aims to maximize the number of Real Time (RT) and Non Real Time (NRT) users that meet their desired Quality of Service (QoS) in the cognitive Long Term Evolution-Advanced (LTE-A). This cognitive LTE-A allows its Component Carriers (CCs) to be combined with licensed CCs from another system. This enables the LTE-A to further expand the available bandwidth for packet transmission. The EM-LWDF algorithm decides the priority of each user on the basis of the desired QoS of each packet, the urgency of each packet, channel quality and the average throughput. The potential of this algorithm is validated via computer simulation where it is able to simultaneously maximize more users that meet their desired QoS in realistic RT and NRT multimedia of the downlink cognitive LTE-A. ABSTRAK: Algoritma penjadualan paket yang dikenali sebagai Enhanced Maximum-Largest Weighted Delay First (EM-LWDF) dicadangkan dalam kertas ini. Ia bertujuan untuk memaksimumkan bilangan pengguna Real Time (RT) dan Non Real Time (NRT) yang memenuhi Kualiti Perkhidmatan yang dikehendaki (QoS) dalam system kognitif Long Term Evolution-Advanced (LTE-A). Kognitif LTE-A ini membolehkan Carrier Component (CC) untuk digabungkan dengan CC berlesen dari sistem lain. Ini membolehkan LTE-A untuk memperluaskan jalur lebar yang tersedia bagi penghantaran paket. Algoritma EM-LWDF menentukan keutamaan setiap pengguna berdasarkan QoS yang dikehendaki dari setiap paket, kecemasan setiap paket, kualiti saluran dan purata penghantaran. Potensi algoritma ini disahkan melalui simulasi komputer di mana ia dapat memaksimumkan lebih banyak pengguna yang memenuhi QoS yang dikehendaki mereka dalam realistik RT dan NRT multimedia dari downlink sistem kognitif LTE-A.

<p>Given that the demand for real-time multimedia contents that require significantly high data rate are getting of high popularity, a new mobile cellular technology known as Long term Evolution-Advanced (LTE-A) was standardized. The LTE-A is envisaged to support high peak data rate by aggregating more than one Component Carriers (CCs) of the same or different frequency bandwidths. Since the inter-band non-contiguous carrier aggregation is likely to be used due to the current frequency allocation, this paper provides a performance study of a number of CC selection algorithms for use in the inter-band non-contiguous downlink LTE-A. It should be noted that CC selection is of paramount importance in the LTE-A operating in backward compatible mode as the LTE-A contains a mixture of the legacy Long Term Evolution (LTE) users that support packets (re)transmission on a single CC and the LTE-A users that utilize more than one CCs for packets (re)transmission. Simulation results demonstrated the efficacy of the Channel-Throughput Aware (CTA) algorithm for maximizing the system capacity without compromising the required Quality of Service of real-time video users.</p>