Multicast Resource Allocation Research Articles

Dynamic resource allocation for multicast in SDM-EON: time-decoupled dynamic path cross talk and joint weight

With the development of the Internet and the rise of multicast, enabling multicast in a space division multiplexing elastic optical network (SDM-EON) is considered highly necessary. This paper focuses on the dynamic resource allocation for multicast in SDM-EON. First, to ensure service survivability and reduce the complexity of inter-core cross talk computation, we design a path-based strict cross talk avoidance routing, modulation, core, and spectrum allocation (PSCA-RMCSA) algorithm. Then, based on PSCA-RMCSA, a joint weight and PSCA-RMCSA (JW-PSCA-RMCSA) algorithm is proposed to further reduce the blocking probability (BBP) of services. Simulation results show that PSCA-RMCSA reduces the BBP by up to 7.55% and the resource allocation time by up to 88.63%, while JW-PSCA-RMCSA reduces the BBP by up to 10.43% and the resource allocation time by up to 82.11%, when compared to the shortest path tree RMSCA.

An Overlapping Coalition Formation Game Based Multicast Scheme in Backhaul-Limited Small Cell Networks

This paper studies the resource allocation for multicast transmission in wireless small cell networks, which allocates appropriate Modulation and Coding Scheme (MCS) on each physical Resource Block (RB). This problem is not trivial due to the impact of interference and the limited wireless backhaul. We first formulate our concerned problem with the objective of maximizing the network throughput. Afterwards, we utilize framed overlapping coalition formulation game theory to design a distributed resource allocation algorithm. We further analyze the stability and convergence of the proposed algorithm. Finally, we conduct extensive simulations to demonstrate that the limited wireless backhaul capacity is an important factor when identifying the optimal multicast resource allocation solution, and our proposed algorithm can significantly improve the multicast throughput.

Multicast Resource Allocation with Opportunistic Scheduling in LTE Networks

Long Term Evolution (LTE) and beyond networks offer high bitrates with low latencies which makes them the best choice to handle the growing demand on multicast mobile services such as video streaming, and news broadcasting. In Conventional Multicast Scheme (CMS), the gain of multicast is exploited by transmitting data to all users simultaneously using the rate of Worst Channel Gain (WCG), which wastes network resources. In this paper, to better balance the tradeoff between the multicast gain and multiuser diversity, we propose a mechanism to select a threshold to split users into two subgroups and exploits the Opportunistic Multicast Scheme (OMS) to transmit the data. Simulation results show that the proposed mechanism improves the multicast performance in terms of increased throughput, decreased delay and Packet Loss Ratio (PLR) compared to existing mechanisms from the literature.DOI: http://dx.doi.org/10.5755/j01.eie.24.5.21850

Joint Coding and Multicast Subgrouping Over Satellite-eMBMS Networks

Mobile satellite services are extremely important when continuity of service is requested while the user is moving over a wide area. A notable example is represented by live TV services, or more in general by the Multimedia Broadcast/Multicast Services (MBMSs) and its evolved version enhanced MBMS. In this paper, we present the combined use of multicast resource allocation schemes based on subgrouping and application layer joint coding to enhance the performance of live video streaming in mobile satellite systems. The reference architecture foresees a satellite-based long term evolution transmission using orthogonal frequency division multiple access in the forward link. The results show that the combined use of multicast subgrouping resource allocation and application layer joint coding allows high-throughput transmissions with satisfactory user quality of experience of the received video over different satellite channel propagation environments.

Resource allocation and rate adaptation for multicast of real-time traffic in MANET

Multicasting is influenced with increasing importance of real-time and multimedia with different quality of service (QoS) requirement. But mobile ad hoc network (MANET) has limited bandwidth and also the physical channel results in unpredictable resource fluctuation and interference. In order to overcome these issues, resource allocation and rate adaption technique for multicast of real-time traffic in MANET is proposed. In this technique, reservation protocol is used while transmitting real-time data packets in order to reserve future slots and hence, it can be deployed in particular time slot. A three hop slot assignment mechanism is adopted to provide an interference free model. Also, normalised transmission rate is used to characterise transmission rate adoption. The benefit of using this technique is that even if a single copy of data is transmitted by sender, multicast receiver can hear the transmitted signal for each multimedia layer.

Resource allocation and rate adaptation for multicast of real-time traffic in MANET

Resource allocation and rate adaptation for multicast of real-time traffic in MANET

Joint Mode Selection and Resource Allocation for Scalable Video Multicast in Hybrid Cellular and D2D Network

Scalable wireless video multicast has been widely studied as an efficient mechanism for real-time video transmission, and scalable video coding alongside adaptive modulation and coding is proposed to address the heterogeneity of networks and user capabilities in next generation mobile communication networks. This paper combines D2D technology with the traditional cellular network to form a hybrid network to improve video subscriber users' experience. The proposed scheme is formulated into a joint mode selection, resource, and power allocation problem based on interference mitigation, which is proven to be NP-hard. Then, we divide it into two sub-problems, where the first one is model selection to maximize the number of D2D users who can access the systems, and the other is to assign appropriate MCS and resource blocks to each video layer. To solve these two problems, we present a greedy algorithm and a heuristic algorithm, respectively. Simulation results show that our hybrid cellular and D2D communications network can effectively increase the capacity of system users, and the mixed network video multicast model can improve the overall system throughput while providing better video quality.

Resource Allocation With Minimum Outage Probability in Multicarrier Multicast Systems

Several innovative applications are emerging that require significant multimedia data transmissions, which unfortunately, current communication systems struggle to provide. In this paper, we examine the high outage tendencies of conventional multimedia multicasting (CVM) due to the bottleneck imposed by the user with minimum signal-to-noise ratio (SNR) and we present a technique based on the statistical approximations of the amortized weighted averaging (AWG) of users’ SNR. For completeness, we propose a suboptimal multicast resource allocation algorithm using memoization with stochastic rounding. We compare the system performance of AWG scheme with the CVM scheme in multicarrier wireless network using our newly derived system outage probability and average throughput as performance metrics. Numerical results not only show that the performance gap of our suboptimal algorithm is reasonably within 10% from the optimal solution, but also show that the AWG scheme admits more users and is more energy efficient than the CVM especially when low power is available to the system.

Multicast Resource Allocation Enhanced by Channel State Feedbacks for Multiple Scalable Video Coding Streams in LTE Networks

The growing demand for mobile multicast services, such as Internet Protocol television (IPTV) and video streaming, requires effective radio resource management (RRM) to handle traffic with strict quality-of-service constraints over Long-Term Evolution (LTE) and beyond systems. Special care is needed to limit system performance degradation when multiple multicast streams are simultaneously transmitted. To this aim, this paper proposes an RRM policy based on a subgrouping technique for the delivery of scalable multicast video flows in a cell. Our proposal enhances the legacy multicast transmission over LTE systems by exploiting multiuser diversity and the users' channel quality feedbacks. Moreover, it is designed to take advantage of the frequency selectivity in the subgroup formation. Simulation results demonstrate the effectiveness of the proposed scheme, which outperforms existing approaches from the literature. It succeeds in achieving higher spectral efficiency and guaranteeing adequate video quality to all multicast receivers and improved quality to those with good channel conditions.

Efficient Resource Allocation Based on Layered Coding in Single Frequency Network with Limited Feedback Scheme

Single frequency network (SFN) can provide Multimedia Broadcast Multicast Service (MBMS) over a large coverage area, so it receives more and more attention from both academia and industry. However, the application of SFN is still restricted by a large number of feedbacks. Therefore, we propose a novel multicast resource allocation algorithm based on limited feedback scheme. In the algorithm, we first design a user limited feedback scheme based on channel gain threshold to effectively reduce feedback load. The scheme determines to which base stations users should report channel state information. Next, to overcome the MBMS capacity limitation drawback, we encode the MBMS data into a base layer and multiple enhancement layers and develop a joint subcarrier and power allocation strategy to maximize the throughput of enhancement layers while guaranteeing the rate requirement of base layer. Simulation results show that the proposed algorithm significantly reduces 83 % of the feedback overhead while achieving a comparable multicast throughput performance to the case of full feedback.

Efficient multicast resource allocation algorithm with limited feedback scheme in single‐frequency networks

Single-frequency network (SFN) can provide multimedia broadcast multicast service (MBMS) over a large coverage area, so it receives more and more attention from both academia and industry. However, the application of SFN is still restricted by a large number of feedbacks. Therefore, the authors propose a novel multicast resource allocation algorithm based on limited feedback scheme. In the algorithm, they first design a user limited feedback scheme based on channel gain threshold to effectively reduce feedback load. The scheme determines to which base stations users should report channel state information. Next, to overcome the MBMS capacity limitation drawback, they encode the MBMS data into a base layer and multiple enhancement layers and develop a joint subcarrier and power allocation strategy to maximise the throughput of enhancement layers while guaranteeing the rate requirement of base layer. Simulation results show that the proposed algorithm significantly reduces 83% of the feedback overhead while achieving a comparable multicast throughput performance to the case of full feedback.

Layered Multicast Resource Allocation with Limited Feedback Scheme in Single Frequency Networks

Single frequency network (SFN) can provide Multimedia Broadcast Multicast Service (MBMS) over a large coverage area, so it receives more and more attention from both academia and industry. However, the application of SFN is still restricted by a large number of feedbacks. Therefore, we propose a novel multicast resource allocation algorithm based on limited feedback scheme. In the algorithm, we first design a user limited feedback scheme based on channel gain threshold to effectively reduce feedback load. The scheme determines to which base stations users should report channel state information. Next, to overcome the MBMS capacity limitation drawback, we encode the MBMS data into a base layer and multiple enhancement layers and develop a joint subcarrier and power allocation strategy to maximize the throughput of enhancement layers while guaranteeing the rate requirement of base layer. Simulation results show that the proposed algorithm significantly reduces 83 % of the feedback overhead while achieving a comparable multicast throughput performance to the case of full feedback.

Strategy-Proof Resource Allocation Mechanism for Multi-Flow Wireless Multicast

Wireless multicast is a promising technology for delivering information from a server to multiple users. Through wireless multicast, the server can fulfill the data requirement of multiple users by simply transmitting a single copy of data contents, which increases the efficient usage of radio resources. This paper considers a multi-flow multicast scenario where a base station (BS) is capable of sending multiple data flows to multiple multicast groups. To configure the multicast and achieve optimal resource allocation, the BS may require the feedback of the channel-quality information (CQI) from the users. The CQI is, in general, the users' private information as only the users can directly measure their channel qualities. However, the selfish users may manipulate the multicast configuration through untruthful feedback to increase their own performance. Regarding this issue, we propose a multicast resource allocation mechanism with the designs of the pricing scheme and the weighted water-filling resource allocation. Our analysis shows that the proposed mechanism can elicit the true CQI from the users (strategy-proofness), avoiding any manipulation of multicast configuration and thereby guaranteeing efficient and fair network operation.

Network selection and resource allocation for multicast in HetNets

In a heterogeneous wireless system, the member stations of a multicast stream may be distributed in many networks within the system. Meanwhile, each member station may have multiple network interfaces available simultaneously. Therefore, the selection of networks for serving the stream and the allocation of radio resources in the selected networks play significant roles in improving the utilization of system resource, especially for the stream with a large group size. In this paper, a novel joint network selection and resource allocation scheme is proposed aiming to minimize the overall resources consumed by the multicast stream in the heterogeneous wireless system. The fundamental idea is to gather the member stations located at the same network region and to transmit the stream with possibly high modulation and coding rates. We first formulate the scheme as a binary integer programming problem, and then derive a computationally efficient Lagrangian-based heuristic algorithm to solve the problem, where the architecture of interworking system is taken into account. Simulation results show that the proposed scheme will cost the minimum system bandwidth compared to other reference schemes.

Joint Resource Allocation for Cellular and D2D Multicast Based on Cognitive Radio

Device-to-device (D2D) communication is an excellent technology to improve the system capacity by sharing the spectrum resources of cellular networks. Multicast service is considered as an effective transmission mode for the future mobile social contact services. Therefore, multicast based on D2D technology can exactly improve the spectrum resource efficiency. How to apply D2D technology to support multicast service is a new issue. In this paper, a resource allocation scheme based on cognitive radio (CR) for D2D underlay multicast communication (CR-DUM) is proposed to improve system performance. In the cognitive cellular system, the D2D users as secondary users employing multicast service form a group and reuse the cellular resources to accomplish a multicast transmission. The proposed scheme includes two steps. First, a channel allocation rule aiming to reduce the interference from cellular networks to receivers in D2D multicast group is proposed. Next, to maximize the total system throughput under the condition of interference and noise impairment, we formulate an optimal transmission power allocation jointly for the cellular and D2D multicast communications. Based on the channel allocation, optimal power solution is in a closed form and achieved by searching from a finite set and the interference between cellular and D2D multicast communication is coordinated. The simulation results show that the proposed method can not only ensure the quality of services (QoS), but also improve the system throughput.

Resource allocation for the cluster-based cooperative multicast in OFDM-based cognitive radio systems

This paper investigates the resource allocation problem for the cluster-based cooperative multicast in orthogonal frequency division multiplexing (OFDM)-based cognitive radio (CR) systems. Aiming at maximizing the system sum rate, an efficient clustering scheme is proposed. It begins with the clustering phase where secondary users (SUs) with good channel conditions are selected as cluster heads, while others decide to which cluster they belong. When the clusters are organized, it turns to a two-stage data transmission phase: in stage 1, the secondary base station (BS) transmits data to the cluster heads; in stage 2, the cluster heads forward the received data to their cluster members. Based on this scheme, a joint subcarrier and power allocation algorithm is proposed. Simulation results show that the proposed scheme significantly outperforms the conventional multicast (CM) as well as the multiple description coding multicast (MDCM) in terms of the system sum rate.

Joint Subcarriers and Power Allocation with Imperfect Spectrum Sensing for Cognitive D2D Wireless Multicast

Wireless multicast is considered as an effective transmission mode for the future mobile social contact services supported by Long Time Evolution (LTE). Though wireless multicast has an excellent resource efficiency, its performance suffers deterioration from the channel condition and wireless resource availability. Cognitive Radio (CR) and Device to Device (D2D) are two solutions to provide potential resource. However, resource allocation for cognitive wireless multicast based on D2D is still a great challenge for LTE social networks. In this paper, a joint sub-carriers and power allocation model based on D2D for general cognitive radio multicast (CR-D2D-MC) is proposed for Orthogonal Frequency-Division Multiplexing (OFDM) LTE systems. By opportunistically accessing the licensed spectrum, the maximized capacity for multiple cognitive multicast groups is achieved with the condition of the general scenario of imperfect spectrum sensing, the constrains of interference to primary users (PUs) and an upper-bound power of secondary users (SUs) acting as multicast source nodes. Furthermore, the fairness for multicast groups or unicast terminals is guaranteed by setting a lower-bound number of the subcarriers allocated to cognitive multicast groups. Lagrange duality algorithm is adopted to obtain the optimal solution to the proposed CR-D2D-MC model. The simulation results show that the proposed algorithm improves the performance of cognitive multicast groups and achieves a good balance between capacity and fairness.

Power and Subcarrier Allocation for Multicast Service in OFDMA Decode-and-Forward Relay Systems

Orthogonal Frequency Division Multiplexing Access (OFDMA) relay system is a promising technique for increasing the capacity and the range of wireless communication systems. Dynamic resource allocation for OFDMA relay systems plays an important role in improving the system performance. However, most of the resource allocation algorithms are designed for the unicast traffics, and resource allocation algorithm for multicast traffics in OFDMA relay systems has received little attention. In this paper, the resource allocation problem for the decode-and-forward relay assisted OFDMA multicast system is considered. Our goal is to maximize the sum rate of the multicast system under the constraints of total power limit and exclusive subcarrier usage. The multicast resource allocation problem is formulated as a mixed integer programming problem. The problem is firstly solved by using Lagrangian dual decomposition method, resulting in an asymptotically optimal joint subcarrier and power allocation algorithm with computational complexity being linear with the number of multicast groups and subcarriers. Furthermore, a low complexity suboptimal resource allocation algorithm is presented to further reduce the computational complexity. Simulation results show that both the proposed optimal and suboptimal algorithms can significantly improve the system performance and the proposed suboptimal algorithm can achieve a near optimal solution.

Energy-Efficient Video Multicast in 4G Wireless Systems

Layer-based video coding, together with adaptive modulation and coding, is a promising technique for providing real-time video multicast services on heterogeneous mobile devices. With the rapid growth of data communications for emerging applications, reducing the energy consumption of mobile devices is a major challenge. This paper addresses the problem of resource allocation for video multicast in fourth-generation wireless systems, with the objective of minimizing the total energy consumption for data reception. First, we consider the problem when scalable video coding is applied. We prove that the problem is NP-hard and propose a 2-approximation algorithm to solve it. Then, we investigate the problem under multiple description coding, and show that it is also NP-hard and cannot be approximated in polynomial time with a ratio better than 2, unless P = NP. To solve this case, we develop a pseudopolynomial time 2-approximation algorithm. The results of simulations conducted to compare the proposed algorithms with a brute-force optimal algorithm and a conventional approach are very encouraging.

Energy-Efficient Resource Allocation and Scheduling for Multicast of Scalable Video Over Wireless Networks

In this paper, we investigate optimal resource allocation and scheduling for scalable video multicast over wireless networks. The wireless video multicasting is a best-effort service which has limited transmission energy and channel access time. To cater for multi-resolution videos to heterogeneous clients and for channel adaptation, we adopt scalable video coding (SVC) with spatial, temporal and quality scalabilities. Our scalable video multicast system consists of a channel probing stage to gather the channel state information and a transmission stage to multicast videos to clients. We formulate the optimal resource allocation problem by maximizing the video quality of the clients subject to transmission energy and channel access constraints. We show that the problem is a joint optimization of the selection of modulation and coding scheme (MCS), and the transmission power allocation. By imposing a quality-of-service (QoS) constraint on the packet loss rate, we simplify the original problem to a binary knapsack problem which can be solved by a dynamic programming approach. Specifically, we first propose a multicast scheduling scheme based on the quality impact of each SVC layer. Guided by the content-aware multicast scheduling, we optimize the resource allocation for each SVC layer sequentially. Solution at each step takes into account of the channel condition, remaining resources, and client requirements. The proposed scheme is of linear complexity and leads to the maximized video quality for the admitted clients, while satisfying the energy budget and channel access constraints. Experiment results demonstrate that our scheme achieves notable video quality improvements for multicast clients, when compared to the state-of-the-art video multicast method.