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Due to the capability of simultaneously delivering the same information to multiple users, the multicast transmission has been widely applied over the satellite networks. Furthermore, more and more information needs to ensure the transmission delay within a predefined bound. However, the satellite networks possess the time-varying characteristics and limited energy, which causes challenges for the low delay multicast design. In this paper, we investigate the energy-efficient delay-bounded (EEDB) multicast problem to accomplish the multicast transmission within the given delay bound, but to consume energy as less as possible. Specially, with the help of the time-expanded graph (TEG), we construct the multicast time-expanded graph (MTEG) through introducing some auxiliary vertices and arcs to accurately depict the across-time multicast transmission and the “wireless multicast advantage”. Then, we formulate the EEDB multicast problem as one combinatorial optimization and propose an iterative heuristic algorithm to achieve the suboptimal multicast scheme. Simulation results are also presented to verify our proposed algorithm.

Summary This paper investigates the multicast transmission for multicast services in high‐throughput satellite (HTS) systems. Considering the multibeam multicast feature of HTSs, cooperative transm...

Immersive virtual reality (VR) applications require ultra-high data rate and low-latency for smooth operation. Hence in this paper, aiming to improve VR experience in multi-user VR wireless video streaming, a deep-learning aided scheme for maximizing the quality of the delivered video chunks with low-latency is proposed. Therein the correlations in the predicted field of view (FoV) and locations of viewers watching 360$^\circ$ HD VR videos are capitalized on to realize a proactive FoV-centric millimeter wave (mmWave) physical-layer multicast transmission. The problem is cast as a frame quality maximization problem subject to tight latency constraints and network stability. The problem is then decoupled into an HD frame request admission and scheduling subproblems and a matching theory game is formulated to solve the scheduling subproblem by associating requests from clusters of users to mmWave small cell base stations (SBSs) for their unicast/multicast transmission. Furthermore, for realistic modeling and simulation purposes, a real VR head-tracking dataset and a deep recurrent neural network (DRNN) based on gated recurrent units (GRUs) are leveraged. Extensive simulation results show how the content-reuse for clusters of users with highly overlapping FoVs brought in by multicasting reduces the VR frame delay in 12\%. This reduction is further boosted by proactiveness that cuts by half the average delays of both reactive unicast and multicast baselines while preserving HD delivery rates above 98\%. Finally, enforcing tight latency bounds shortens the delay-tail as evinced by 13\% lower delays in the 99th percentile., Accepted for publication in IEEE Transactions on Communications 17 pages, 10 Figures

Multimedia traffic is predicted to account for $\mathbf {82}$ % of the total data traffic by the year 2020. With the increasing popularity of video streaming applications like YouTube, Netflix, Amazon Prime Video, popular video content is often required to be delivered to a large audience simultaneously. Multicast transmission can be used to cater to such applications efficiently. The common content can be transmitted to the users on the same resources resulting in considerable resource conservation. This paper proposes various schemes for efficient grouping and resource allocation for multicast transmission in LTE. The optimal grouping and resource allocation problems are shown to be NP-hard and so, we propose heuristic algorithms for both these problems. We also formulate a Simulated Annealing based algorithm to approximate the optimal resource allocation for our problem. The LP-relaxation based resource allocation proposed by us results in allocations very close to the estimated optimal.

We investigate physical layer security in massive multiple-input multiple-output multicast transmission where the base station only knows the statistical channel state information of the legitimate user terminals and the eavesdropper. We first introduce a tight lower bound of the achievable secrecy multicast rate as the design objective. Then, we find the closed-form transmit directions, i.e., the eigenvectors of the optimal multicast transmit covariance matrix, which simplifies the matrix-valued multicast transmit strategy design into a beam domain power allocation problem. We further propose an efficient iterative power allocation algorithm with guaranteed convergence to a local optimal solution by invoking the concave-convex procedure. We also derive the deterministic equivalent of the optimization objective to reduce the computation complexity. Numerical results demonstrate the performance gains of the proposed approach over the conventional approach.

This letter investigates the robust beamforming design for multigroup multicast in a backhaul-limited cloud radio access network. Users requesting the same content form a multicast group, served by remote radio heads (RRHs) cooperatively. Each RRH acquires the requested contents from baseband unit via backhaul links. We first formulate the robust beamforming design as maximizing the sum of the minimum rate of users in each multicast group under the transmission power and backhaul constraints. Due to the introduction of the channel estimation error and inter-user interference, the considered problem becomes more complex and difficult to address directly. To overcome these difficulties, convex approximation methods are adopted to transform the original problem into convex one. Then, an effective optimization algorithm is developed to address the resulting problem. Numerical results demonstrate the effectiveness of the proposed robust beamforming design of multigroup multicast transmission.

Multicast transmission plays a vital role in reducing wireless data traffic. However, the conventional multicast beamformer design mainly relied on suboptimal solutions found by numerical solvers which failed to provide analytic design insights, due to the analytic intractability of the multicast beamformer design problem. In this paper, we explore a rank-one multicast beamformer design for a single group multicasting scenario and derive a closed-form solution to help how the channel parameters affect the beam direction and the achieved SNR. To this end, we first revisit the Karush-Kuhn-Tucker (KKT) necessary condition of the single group multicasting problem. Then, we derive a closed-form solution for a multicast beamformer, which satisfies KKT necessary conditions, for given active constraints. Finally, we select the best beamformer among the ones from different active constraints. It is shown that the proposed multicast beamformer achieves better than or at least comparable performance to the existing sub-optimal solutions.

International audience; Reliable group video call is one of the main services offered by future Mission-Critical Communications (MCC). To support its requirements, coordinated multi-point transmission in multi-cell environments is an attractive feature for MCC over Multimedia Broadcast Multicast Services owing to its potential for coverage improvement and multicast transmission. In such a scheme, full cooperation among all cells of an area achieves the highest cooperative gain, but has stringent impact on system capacity. A trade-off in the cluster's size of serving cells thus arises between high Signal to Interference plus Noise Ratio (SINR) and network capacity. In this paper, we formulate an optimization problem to maintain an acceptable system blocking probability, while maximizing the average SINR of the multicast group users. For every multicast group to be served, a dynamic cluster of cells is selected based on the minimization of a submodular function that takes into account the traffic in every cell through some weights and the average SINR achieved by the group users. Traffic weights are then optimized using a modified Nelder-Mead simplex method with the objective of tracking a blocking probability threshold. The proposed clustering scheme is compared to full cooperation and to Single-Cell Point-To-Multipoint (SC-PTM) schemes. Results show that dynamic clustering offers the best trade-off between coverage and capacity for MCC.

Adopting full frequency reuse in High Throughput Satellite (HTS) systems is expected to cope with huge communication demands and large user populations. Moreover, a kind of multicast transmission, which embeds the data of several users in each frame, can be employed to increase the efficiency of HTS systems. Multicast precoding is usually utilized in such systems to mitigate the co-frequency interference between beams and improve the efficiency of transmission. In this context, considering that the number of users may exceed the number of available communication resources in the system, we investigate user scheduling for the multicast transmission in HTS systems with full frequency reuse and multicast precoding. We perform user scheduling according to the user channel state information and decouple the scheduling problem into two phases: intra-beam and inter-beam scheduling. Intra-beam scheduling determines the users involved in the transmission of each frame with the purpose of reducing the influence of the multicast fashion. For intra-beam scheduling, we put forth a fixed-size user grouping algorithm. In contrast to previous studies, this algorithm takes the interference among beams into consideration during the scheduling. In inter-beam scheduling, user groups belonging to different beams are scheduled to improve the performance of the multiplexed transmission. An inter-beam scheduling algorithm is proposed to improve the fairness among users. The simulation results verify the superiority of the proposed algorithms in terms of fairness and spectral efficiency.

This paper proposes a maritime transmission scheme in integrated satellite-maritime networks, where the satellite multicast and relay cooperation cooperatively provide the ubiquitous broadband coverage for the whole sea area. Under the proposed network, the maritime users that request the same content or belong to the same fleet can be divided into one user group. Besides, the satellite provides multicast services for the all user groups, while the relay nodes retransmit the signal to other users to reduce the satellite communication cost of user group. However, since the network performance is strongly correlated with satellite links and relay nodes, it is difficult to find out the optimal cooperation solution with low complexity. Meanwhile, the user groups work in the same carrier frequency, which inevitably causes the co-channel interferences among groups. Considering these factors, we propose a cooperative access and power allocation algorithms, respectively. The cooperative access algorithm is based on channel quality and considers the channel quality of satellite and relay node simultaneously. The simulation results show that the proposed scheme can effective improve system performance compared with existing scheme.

In this paper, we consider the multicast transmission of a real-time Internet of Things (IoT) system, where an access point (AP) transmits time-stamped status updates to multiple IoT devices. Different from the existing studies that only considered multicast transmission without deadlines, we enforce a deadline for the service time of each multicast status update, taking into account both the fixed and randomly distributed deadlines. In particular, a status update is dropped when either its deadline expires or it is successfully received by a certain number of IoT devices. Considering deadlines is important for many emerging IoT applications, where the outdated status updates are of no use to IoT devices. We evaluate the timeliness of the status update delivery by applying a recently proposed metric, named the age of information (AoI), which is defined as the time elapsed since the generation of the most recently received status update. After deriving the distributions of the service time for all possible reception outcomes at IoT devices, we manage to obtain the closed-form expressions of both the average AoI and the average peak AoI. Simulations validate the performance analysis, which reveals that the multicast transmission with deadlines achieves a lower average AoI than that without deadlines and there exists an optimal value of the deadline that can minimize the average (peak) AoI. Results also show that the fixed and random deadlines have respective advantages in different deadline regimes., Comment: arXiv admin note: substantial text overlap with arXiv:2002.02125

We consider the multicast transmission of a real-time Internet of Things (IoT) system, where a server transmits time-stamped status updates to multiple IoT devices. We apply a recently proposed metric, named age of information (AoI), to capture the timeliness of the information delivery. The AoI is defined as the time elapsed since the generation of the most recently received status update. Different from the existing studies that considered either multicast transmission without hard deadlines or unicast transmission with hard deadlines, we enforce a hard deadline for the service time of multicast transmission. This is important for many emerging multicast IoT applications, where the outdated status updates are useless for IoT devices. Specifically, the transmission of a status update is terminated when either the hard deadline expires or a sufficient number of IoT devices successfully receive the status update. We first calculate the distributions of the service time for all possible reception outcomes at IoT devices, and then derive a closed-form expression of the average AoI. Simulations validate the performance analysis, which reveals that: 1) the multicast transmission with hard deadlines achieves a lower average AoI than that without hard deadlines; and 2) there exists an optimal value of the hard deadline that minimizes the average AoI.

The demand of massive access to the same multimedia content at the same time is one major challenge for next-generation cellular networks in densely-packed urban areas. The content-aware multicast transmission strategies provide promising solutions to such use cases involving many mobile users trying to fetch the same data. In this work, we consider multigroup multicast transmission with a common message (e.g., multimedia content), in which different multicast groups are interested along with their private multicast messages. We further assume that a relay helps the cellular base station (BS) disseminate multicast content to the users experiencing high path loss and/or blockage. We propose superposition and concatenated coding schemes, denoted by SC and CC, respectively, to transmit the common and private multicast messages. In order to maximize max-min fair (MMF) rates, we design a novel low-complexity alternating-optimization algorithm to compute transmit and relay precoders. We also propose rate-splitting (RS) alternatives of SC and CC schemes together with an iterative algorithm to derive dedicated transmit and relay precoders so as to maximize MMF rates. We rigorously evaluate the performance of the proposed transmission schemes and precoders, and verify the superiority of RS-based schemes in overloaded scenarios without any saturation with increasing signal-to-noise ratio.

We consider the problem of downlink multicast transmission of user data in massive MIMO systems. Due to the nature of multicast transmission, the common data rate in a multicast group is constrained by that of the user with the worst Signal-to-Noise-Ratio (SNR). As a consequence, serving a large number of users in a single multicast group might degrade the system performance. To overcome this drawback, utilizing spatial degrees of freedom offered by a large number of transmit antennas, we propose to dynamically divide the set of serving users into multiple multicast groups and jointly design the user grouping pattern and co-channel beamforming vectors of these groups. Given the NP-hardness of the considered problem, we decompose it into a multi-group multicast beamforming subproblem and a user grouping subproblem. We proposed several low-complexity methods to iteratively solve these subproblems in order to obtain a suboptimal solution to the original problem. Simulation results show that our proposed GRouping And Beamforming (GRAB) scheme achieve significantly higher average sum-rate performance compared to that of the existing multicast schemes.

In this paper, we investigate the downlink cooperative multigroup multicast transmission in the integrated terrestrial-satellite network, in which base stations (BSs) and the satellite provide the multicast service for ground users in a cooperative manner while reusing the entire bandwidth. For both terrestrial BSs and the satellite, multiantennas are equipped and beamforming techniques are utilized for improving the system performance. Based on the architecture, we formulate a weighted max–min fair (MMF) beamforming design problem to jointly optimize the beamforming vectors of BSs and the satellite, which is solved based on the relation between the quality of service problem and the MMF problem. When it comes to the large scale case, where large numbers of BSs are distributed within the coverage of the satellite, we propose a time division cooperative multigroup multicast scheme consisting of two phases for the BSs and the satellite. Then, an iterative algorithm is proposed to solve the weighted MMF problem in the time division case. Finally, numerical results are provided to evaluate the cooperative multicast schemes as well as the proposed algorithms.

This paper considers a two-user asynchronous multicast scenario where both users request the same content at different time instances, and a base station simultaneously serves them with nonorthogonal transmission. To serve the asynchronous requests of the same content, we develop three nonorthogonal transmission schemes. The first scheme serves the asynchronous requests by unicast transmission and the second scheme enables multicast transmission for the asynchronous requests based on interference decoding capability at receiver. The third scheme combines the first and second schemes. For the three proposed schemes, we formulate completion time minimization problems that aim to minimize the time required to complete serving users, while ensuring a given quality constraint of streaming content. For each scheme, the feasibility condition in terms of transmit power and optimal rate control are investigated. In addition, we analytically compare the performance of the proposed schemes, and additionally, propose an opportunistic transmission that opportunistically switches three proposed schemes depending on the channel and power conditions.

Multicast communication is a key technology for wireless mesh networks. In order to reduce co-channel interference in multicast transmission, we jointly study multicast tree construction and channel assignment in this paper. First, interference in multicast is analyzed and measured with considerations of hidden node problem and user coverage. Then, an algorithm called CIOMT is proposed to construct multicast routing tree, In which we find the path with minimum interference to root and add it to the constructing multicast tree, give an upper limit to the source-to-destination distance for QoS consideration, and tree structure is optimized to relieve interference among multicast links. Moreover, we propose a channel assignment algorithm for the constructed multicast tree with the name CIOCA. In CIOCA algorithm, in order to provide good service to the users as much as possible, we take the user coverage of each destination as the top priority in channel assignment, and the nodes are assigned the sending channels by descending order of priority. In each step, we find the channel with minimum interference to the whole tree, and assign it to the related nodes. For making full use of spectrum resources, the non-overlapping and overlapping channels are both taken into consideration. At last, simulation is done, and the results show the effectivity of the proposed multicast routing scheme. As far as user satisfaction is concerned, the proposed scheme has much better performance than the other two classic algorithms.

This paper presents a reliable and energy-efficient hybrid screen mirroring multicast system for sharing high-quality real-time multimedia service with adjacent mobile devices over WiFi network. The proposed system employs overhearing-based multicast transmission scheme with Raptor codes and NACK-based retransmission to overcome well-known WiFi multicast problems such as low transmission rate and high packet loss rate. Furthermore, to save energy on mobile devices, the proposed system not only shapes the screen mirroring traffic, but also determines the target sink device and Raptor encoding parameters such as the number of source symbols, symbol size, and code rate while considering the energy consumption and processing delay of the Raptor encoding and decoding processes. The proposed system is fully implemented in Linux-based single board computers and examined in real WiFi network. Compared to existing systems, the proposed system can achieve good energy efficiency while providing a high-quality screen mirroring service.

The orthogonal frequency division multiple access (OFDMA)-based cooperative multicast (CM) technology realizing the intra-cooperation of multicast group (MG) has improved the performance in throughput and coverage. In the MG scenario, users are uniformly distributed. Due to the small effective transmission range of relay user (RU), the cooperation is hindered, which limits the performance of CM. Therefore, non-orthogonal multiple access (NOMA)-based two MGs joint cooperative opportunistic multicast scheme (termed as COM-NOMA) is proposed. In COM-NOMA scheme, two MGs are served as one quasi-MG. First, on the same frequency band, base station (BS) opportunistically multicasts the superposition signal, which is formed by two MGs' signals, to the users with good channel conditions in the two MGs using NOMA way. Second, some successfully receiving users are selected as RUs. The superposition signal is forwarded to the other users by Device-to-Device multicast way. Then, according to the coverage ratio of BS and the decode condition of NOMA, the signal to interference and noise ratio threshold for RU selection is given. Finally, the spectral efficiency of COM-NOMA is analyzed and the approximate expression of system coverage ratio is derived. The simulation results show that, spectral efficiency at unit transmit power (spectral efficiency per watt) and system coverage ratio is improved in comparison with other OFDMA-based CM schemes.

In this paper, we provide an implementation and thorough performance evaluation of the RFC 6775 optimized Neighbor Discovery (ND) protocol. RFC 6775 was developed by the Internet Engineering Task Force (IETF) to standardize IPv6 neighbor discovery over Low power Wireless Personal Area Networks (6LoWPAN). First, we investigate and analyze the basic RFC 4861 ND, developed for general networks running IPv6. We explain why such a basic ND protocol is inefficient and sometimes impractical for 6LoWPANs. This is because of (i) its heavy use of multicast transmission, and (ii) being originally not designed for IEEE 802.15.4 non-transitive wireless environments in which all nodes are not necessarily within range of each other. Second, we overview and explain the optimized RFC 6775 ND. Third, we implement such an optimized ND on the widely used Contiki OS. Finally, we evaluate the performance of our implementation of the optimized ND protocol and compare it with the current RFC 4861-based ND implementation. Our results show that the implementation of the optimized ND protocol reduces the number of the exchanged control messages in the network by up to 70% compared to RFC 4861-based ND. Moreover, multicast ND control messages are reduced by 30% to 70%. We show that the RFC 6775 optimizations alleviate network congestion, enhance the delivery ratio of ND packets to almost 100% and save more power. Even in the case of variable node reachability, the optimized ND protocol shows a better performance compared to the RFC 4861 basic ND.

The 60-GHz bands target multi-gigabit rate applications, such as high definition video streaming. Unfortunately, to provide multicast service, the strong directionality required at 60 GHz precludes serving all clients in a multicast group with a single transmission. Instead, a multicast transmission is comprised of a sequence of beam-formed transmissions (a beam group) that together cover all multicast group members. In this paper, we design, implement, and experimentally evaluate scalable directional multicast (SDM) as a technique to 1) train the access point with per-beam per-client RSSI measurements via partially traversing a codebook tree. The training balances the objectives of limiting overhead with collecting sufficient data to form efficient beam groups. 2) Using the available training information, we design a scalable beam grouping algorithm that approximates the minimum multicast group data transmission time. We implement the key components of SDM and evaluate with a combination of over-the-air experiments and trace-driven simulations. Our results show that the gains provided by SDM increase with group size and provide near-optimal group selection with significantly reduced training time, yielding up to 1.8 times throughput gains over exhaustive-search training and grouping.

The broadband wireless network provides an efficient solution for both data reliability and network congestion to meet the demand of the increasing number of mobile users. However, due to dense deployment of nodes, interference and data dissemination problems occur which result in unreliable packet delivery during data transmission in smart cities. All this creates problem in efficient data transmission. In order to solve this problem, in this work, we propose a novel Code-Encoding and Decoding (C-ED) mechanism for IEEE 802.16 networks that helps to mitigate the problem of data dissemination by using minimal number of channels. The proposed C-ED mechanism provides a reliable packet delivery during multicast transmission. As the smart cities are connected with complex networks, our scheme utilizes the existing channel assignment strategies to assign a minimal number of channels to the network and transmit the data using the proposed C-ED mechanism. To illustrate the effectiveness of the proposed C-ED mechanism, it is evaluated by combining it with the existing channel assignment strategies i.e., clique partitioning and random. The simulation results show that the C-ED mechanism with clique partitioning provides improved quality of service than random channel assignment. The C-ED mechanism is compared with Luby Transform (LT) codes which result in reduced transmission delay and improved throughput for a complex network.

With the rapid evolution of multimedia and real-time applications like audio/video conferencing, certain quality-of-service (QoS) should be guaranteed for the multicast transmission. For the given delay-constrained multicast request, the goal of delay-constrained survivable multicast routing problem (DCSMRP) is to provide the primary multicast tree and protecting resources so that after recovering from the link (node)-failure, the recovered tree can satisfy the delay constraint. In this article, the DCSMRP with a single node-failure case on wavelength-division multiplexing (WDM) networks is considered. Three node-failure protecting methods, includes node-disjoint trees (NDT), node-encircling p-cycles (NEPCs) and failure-independent path protecting p-cycles (FIPP p-cycles) are used in this article. For each protecting method, an algorithm is designed to solve the studied problem. Simulations are also conducted to evaluate the performance of the proposed algorithms.

International audience; In this paper, we present new adaptive automatic repeat request (ARQ) schemes for wireless broadcast/multicast combining erasure coding (EC) and packet retransmission. Traditional approaches rely on retransmitting the lost packets in a point-to-point or point-to-multipoint mode. The main idea behind the presented protocols is to retransmit adaptive combinations of the lost packets using EC, which can help several receivers to recover the lost information with fewer retransmission attempts.We propose two versions of EC-based ARQ protocols, and investigate theoretically the corresponding transmission bandwidths in different contexts. We show through simulation results the efficiency of the proposed protocols with respect to conventional ARQ strategies and new published ARQ works for broadcast/multicast. Finally, a new sliding window NACK feedback policy is presented for the case of a high number of receivers to avoid the feedback implosion problem.

We consider the problem of multicast transmission in cooperative cellular systems, where a base station (BS) aims at conveying a common message to a set of user equipments (UEs) that are also connected with each other via device-to-device (D2D) links. Assuming statistical channel knowledge at the BS, we design a two-phase scheme that exploits multi-antenna transmission at the BS and D2D communications between the UEs to achieve a non-vanishing multicast rate when the number of UEs grows large. This represents a non-trivial extension of our previous work, which is restricted to the case of instantaneous channel knowledge at the BS (and is thus impractical for dense networks). Finally, we study the scaling of the resulting multicast rate as a function of the number of UEs and BS antennas for different practical scenarios.

Multicast transmission is an attractive solution when a large number of users receive the same content in a wide area, for example, as with mobile TV. Ever since the multimedia broadcast multicast service (MBMS) was introduced in the 3rd Generation Partnership Project (3GPP), continuing work on the multicast transmission has been done and its importance is growing in the fifth generation (5G) cellular networks. The use cases of multicast transmission have been enlarged from mobile TV and public safety to vehicular-to-everything (V2X) and unmanned aerial vehicles (UAV). Recently, for group communications in public safety networks and for geographical information sharing in automotive, airborne and social networks, multicast transmission has been targeted at fewer users in a relatively small area, which has stimulated extensive research on the single-cell multicast transmission scheme. In the proposed single-cell multicast transmission scheme, a supplementary multicast channel is additionally assigned in a single-cell multicast transmission scheme to exploit channel diversity. The resource allocation is adaptive to the channel variations of the users (responsive to users QoS needs), using channel feedback from the users, in contrast with previous approaches where resources were determined conservatively. An optimal resource allocation problem to minimize the required bandwidth while enabling every user to obtain the target multicast rate is formulated as a convex problem and an iterative algorithm is proposed in a computationally efficient way. Performance is evaluated mathematically and through intensive simulations, where other cell interference is considered using a fluid model. The proposed single-cell multicast transmission scheme provides benefits in comparison to existing multicast schemes in the simulations, under a set of various parameters including the number of multicast users and channel correlation between the multicast channels.

As the number of users or services continues to increase, limited bandwidth resources become a huge challenge for power wireless communication networks. The communication protocols widely used in the current distribution network have unclear data meanings, less correlation between data, and inability to interoperate between terminals, which is a bottleneck restricting the development of smart distribution networks. With the development and implementation of the IEC 61850 standard, more and more power service are sent in the form of broadcast and multicast. Among them, the GOOSE (generic object oriented substation event) service is used to transmit events such as real-time trip signals that require fast delivery of message information, and real-time performance is its main feature. However, in the multicast transmission of the power service carried by the existing transmission mode, there is a serious contradiction between resource utilization and the quality of services (QoS) of users. Therefore, in order to balance the QoS with poor signal quality in SFN (Single Frequency Network) transmission mode and to solve the problem of resource allocation being limited by the worst QoS, this paper proposes a hybrid transmission mode combining PTP (point to point) and SFN transmission. In addition, in order to improve resource utilization efficiency, we design a new transmission mode selection algorithm focus on the improvement of spectrum efficiency. The optimal solution obtained through greedy algorithms is the best transmission mode scheduling strategy. The simulation results show that the MIX (mixed transmission mode) effectively reduces the impact of poor QoS users on system performance when the number of users increases. At the same time, the transmission mode selection algorithm can save system resources more effectively than the traditional selection algorithm (PTP and SFN mode).

Multicast transmission has been gaining importance as an efficient means of delivering bandwidth hungry video content and is expected to become an integral part of cellular networks worldwide. This has resulted in the need for generalized allocation algorithms that are capable of handling multiple multicast and unicast services with different Quality of Service (QoS) requirements. In this paper, we propose such a Vickrey-Clarke-Groves (VCG) auction based resource allocation and pricing algorithm. The proposed algorithm takes allocation decisions based on the QoS requirements of the end users for maximizing the system social utility. Even though the users in a multicast group are served on the same PRB, requirements of each individual user are taken into consideration while making the allocation decisions. The proposed algorithm ensures that the users report their true valuations of the system resources. VCG auctions provide a general framework for designing truthful optimal mechanisms. However, in many cases, VCG auction turns out to be NP-hard. In this paper, we propose an efficient, polynomial time implementation of the proposed VCG mechanism. Using simulations, we show that the algorithm successfully meets the unique demands of all unicast and multicast services.

In this paper, we present a novel mobile edge computing (MEC) model where the MEC server has the input and output data of all computation tasks and communicates with multiple caching-and-computing-enabled mobile devices via a shared wireless link. Each task request can be served from local output caching, local computing with input caching, local computing or MEC computing, each of which incurs a unique bandwidth requirement of the multicast link. Aiming to minimize the transmission bandwidth, we design and optimize the local caching and computing policy at mobile devices subject to latency, caching, energy and multicast transmission constraints. The joint policy optimization problem is shown to be NP-hard. When the output data size is smaller than the input data size, we reformulate the problem as minimization of a monotone submodular function over matroid constraints and obtain the optimal solution via a strongly polynomial algorithm of Schrijver. On the other hand, when the output data size is larger than the input data size, by leveraging sample approximation and concave convex procedure together with the alternating direction method of multipliers, we propose a low-complexity high-performance algorithm and prove it converges to a stationary point. Furthermore, we theoretically reveal how much bandwidth gain can be achieved from computing and caching resources at mobile devices or the multicast transmission for symmetric case. Our results indicate that exploiting the computing and caching resources at mobile devices as well as multicast transmission can provide significant bandwidth savings., Comment: submitted to IEEE Trans. Wireless Communications. arXiv admin note: text overlap with arXiv:1807.05536

Pushing contents from content providers (CPs) directly to user equipments (UEs) during off-peak hours can significantly reduce the incurring traffic during peak hours. Both wired and wireless transmission costs are considerable in this scenario, especially in current cellular networks where the backhaul is regarded as a bottleneck of transmission. In order to alleviate the traffic pressure over the network without loss of users' quality of experience, this paper presents a joint wired and wireless transmission scheme which considers grouping, subchannel allocation, wired routing, and wired bandwidth allocation. An iterative algorithm is proposed to achieve the tradeoff between those two kinds of traffic. The users in the same group are served by a single multicast transmission from a base station (BS), while the BSs which multicast the same content form a multicast tree in backbone wired network. Compared with traditional unicast scheme, our approach can reduce the wired, wireless, and total traffic by 23%, 46%, and 34% at most according to the simulation results.

Non-orthogonal multiple access (NOMA), as a promising technology in 5G, can effectively improve the spectrum efficiency and user speed. The performance of multicast services in mobile communication networks is limited by the rate of the worst user, while NOMA can improve the quality of services for optimal channel users while guaranteeing the rate of the worst user of multicast group through power domain reuse. We focus on power allocation algorithms for NOMA based layered multicast transmission in this paper, with the purpose of maximizing sum rate in multicast system while giving attention to user fairness under the constraint of minimum rate and total transmit power. Based on layered multicast scene, a corresponding joint optimization algorithm for user group formation and power allocation is proposed. The effects of noise, user channel gain and power ratio on system performance were analyzed by means of theoretical analysis and simulation. Simulation results show that this algorithm further improves the sum rate of the system.

This paper discusses multicast schemes in cellular networks based on rateless codes and cooperative relaying technologies. Unlike fixed-rate codes, rateless codes do not require channel state information at transmitters or feedback of successful reception of individual packets from recipient user equipment (UEs). Cooperative relaying among a group of multicast recipient UEs can further improve wireless multicast service. In the proposed cooperative multicast (CM) scheme, after part of the recipients have decoded the source message of the base station (BS), these recipients can act as cooperative relays (CRs) and simultaneously transmit the decoded information to other recipients. The CM process stops after all the recipients have reliably decoded the message. If the CRs use different fountain codes, the other recipients can accumulate the mutual information from the BS and the CRs. If the CRs use the same fountain code as used by the BS, the recipients can only accumulate the received energy. By comparing with the conventional direct transmission based multicast scheme, the transmission delay, the energy consumption, and the spectrum efficiency performances of the proposed CM schemes are evaluated. The simulation results show that the mutual information accumulation (MIA) based CM scheme outperforms the energy accumulation (EA) based CM scheme in the spectrum and energy efficiency. This is because the MIA approach acquires better time delay performance but consumes less energy than the EA approach.

We consider the multicast scheduling problem for the block transmission of packets in a heterogeneous network using a half-duplex relay station (RS). The RS uses random linear coding to efficiently transmit packets over time-varying multicast channels. Our goal is to minimize the average decoding delay. Because of the half-duplex operation, at each time slot, the RS must decide to either: 1) fetch a new packet for encoding from the base station or 2) multicast a coded packet to wireless users. Thus, optimal scheduling hinges on exploiting multicast opportunities while persistently supplying the encoder (at the RS) with new packets. We formulate an associated fluid control problem and show that the optimal policy incorporates opportunism across multicast channels, i.e., the RS performs a multicast transmission only if the collection of channel conditions is favorable; otherwise, it performs a fetch. Based on the fluid policy, we propose an online algorithm. We prove that our algorithm asymptotically incurs no more than 4/3 and 2 times the optimal delay, for two-user and arbitrary number of user system, respectively. Simulation results show that, in fact, our algorithm’s performance is very close to theoretical bounds.

In order that multicast routing characteristics is reflected in wireless mesh networks, multicast routing metric is required for quantifying the multicast tree cost under wireless environments. This paper proposes a new multicast routing metric considering receiver's different characteristics of link quality on a wireless multicast channel as well as wireless multicast advantage. The proposed multicast-tree transmission ratio quantifying the multicast tree cost represents the product of the multicast transmission ratios of all nodes in the constructed multicast tree. In this paper, we also propose a wireless multicast routing which constructs the multicast tree by maximizing the multicast-tree transmission ratio in wireless mesh networks with multiple gateways and design the multicast routing protocol based on AODV protocol. Since the multicast tree by our wireless proposed routing algorithm contains the nodes having maximum multicast-node transmission ratio, our proposed multicast routing shows a higher delivery ratio and a lower average delay than original multicast AODV and the multicast routing with minimizing the forwarding nodes in its multicast tree. In comparison with other multicast routings, simulation results show that the proposed multicast heuristics maximizing the multicast-tree transmission ratio construct a cost-effective multicast tree in terms of its delivery ratio, average delay, and required network resources.

Previous works on multicast capacity mainly focus on deriving asymptotic order results in large-scale wireless networks. While they can explore the general scaling laws of throughput capacity, it is also of great interest for practical concern to predict the exact achievable throughput in networks with an arbitrary finite number of nodes. In this paper, we investigate the nonasymptotic throughput and delay of multihop wireless networks for multicast applications wherein for each source node, $k$ nodes are randomly selected as receivers. It is challenging for the exact performance analysis since multicast transmission has a dynamic nature due to the following factors: 1) random distribution of nodes; 2) bursty traffic arrivals; and 3) different timescales for transient analysis. To tackle the problem, we propose an explicit analytical model and develop a multicast routing scheme, which accounts for these aspects. With our proposed model, we derive lower bound (LB) and upper bound (UB) on nonasymptotic multicast throughput and delay using stochastic network calculus. We show that the performance results hold for all timescales and network sizes and are strongly correlated to data burstiness and the number of receivers. While we investigate from a nonasymptotic point of view, our results can also cover the asymptotic scaling laws. Simulations are conducted to further verify the accuracy of the analytical bounds.

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.

Multicast transmission based on real-time network state information is a resource-friendly technique to improve the energy efficiency and reduce the traffic burden for cellular systems. This paper evaluates the effectiveness of this technique for downlink transmissions. In particular, a scenario is considered in which multiple mobile users (MUs) asynchronously request to download one common message locally cached at a base station (BS). Due to the randomness of both the channel conditions and the request arrivals from the MUs, the BS may choose to intelligently hold the arrived requests, especially when the channel conditions are bad or the number of requests is small, and then serve them in one shot later via multicasting. Clearly it is of great interest to balance the delay (incurred by holding the requests) and the energy efficiency (EE, defined as the energy cost per request), and this motivates us to quantify the fundamental tradeoff for the proposed “hold-then-serve” scheme. For the scenario with single channel and unit message sizes, it is shown that for a fixed channel bandwidth, the delay-EE tradeoff reduces to judiciously choosing the optimal stopping rule for when to serve all the arrived requests, where the effect of the bandwidth on the achievable delay-EE region is discussed further. By using optimal stopping theory, it is shown that the optimal stopping rule exists for general Markov channel models and request arrival processes. Particularly, for the hard deadline and proportional delay penalty cases, it is shown that the optimal stopping rule exhibits a threshold structure, and the corresponding threshold in the former case is time varying while in the latter case it is a constant. Finally, for the more general scenario with multiple channels and arbitrary message sizes, the optimal scheduling is formulated as a Markov decision process problem, where some efficient suboptimal scheduling algorithms are proposed.

Multicasting is an efficient solution for transmitting data to a group of users, which leads to the minimal network requirements. However, in real scenario both type of users (unicast and multicast) will exist in the network. Therefore, an appropriate resource allocation method is necessary to satisfy the Quality of Service (QoS) requirements of each user using these services. This paper proposes a resource allocation method to improve the performance of real time service users in spite of their transmission mode is unicast or multicast. If the user is in unicast transmission, the transmission rate is chosen based on the feedback from the user and if the user is in multicast transmission, then the resource allocation is done by subgrouping and adopting different transmission rates. Genetic algorithm is performed on subgroup formation such that the overall rate of the group should be maximized. From the simulation results, it is inferred that there is 46% increase in the average throughput and 10% reduction in delay for the real time users when compared to conventional resource allocation method.

In this paper, we propose a hybrid decode-forward & amplify-forward relaying with opportunistic layered multicast (HDAF-OLM) scheme for a cellular system with multiple relays and multiple users. The scheme integrates hybrid decode-forward and amplify-forward with non-orthogonal multiple access transmission (HDAF-NOMA) scheme and layered multicast transmission into one strategy. Besides, a novel multicast partitioning analysis combined with this scheme is studied and we obtain the maximum transmission rates of a basic multicast stream (BMS) and an enhanced multicast stream (EMS) for fixed number of selected users. Simulation results show that the proposed multicast partitioning method in the HDAF-OLM scheme can achieve larger maximum transmission rates, larger system average throughput and lower delay as compared to conventional multicast scheme. Meanwhile, the HDAF-OLM scheme can also achieve larger total system capacity than traditional scheme.

Device-to-device (D2D) multicast communication is considered as a promising technology to realize the innovative content-aware applications in the fifth generation (5G) networks, such as multimedia multicast service and group-based machine type communications (MTC) applications. Under such scenarios, mobile devices (MDs) that are interested in the same content can be clustered as a group and transmit cooperatively via multiple hops to achieve efficient content distribution. Such multi-hop multicast transmission helps to relief traffic pressure in cellular networks and improve the quality of service for cell edge users. However, it requires careful design of the clustering scheme to ensure delay performance and energy efficiency. In this paper, we propose a multicast clustering algorithm for multi-hop communications. As for each hop, we select a combination of nodes to act as cluster heads (CHs) and multicast the content to a group of next-hop users by jointly considering achievable multicast data rate, remaining operation time and end-to-end delay. In the case of overlapping clusters, we propose a cluster member (CM) reassignment criteria to minimize transmission redundancy. Simulation results show that the performance of our proposed clustering algorithm is competitive in terms of delay and robustness.

Narrowband IoT (NB-IoT) is a new cellular network technology that has been designed for low capability, low power consumption devices that are expected to operate for more than 10 years on a single battery. These types of devices will be inexpensive (less than $5) and deployed on massive scales. This long life expectancy will lead to the need for occasional software updates, to very large groups of devices. While a new multicast mechanism has recently been proposed for the efficient multicast transmission of such updates, it assumes that devices can be grouped together and synchronized in order to receive the multicast data. In this paper, we explore three different approaches to achieve device grouping, with different trade-offs between bandwidth usage, energy consumption and compliance with the NB-IoT standard. To assess the performance of each approach, we conducted a thorough experimental evaluation under realistic operating conditions.

Computation task service delivery in a computing-enabled and caching-aided multi-user mobile edge computing (MEC) system is studied in this paper, where a MEC server can deliver the input or output datas of tasks to mobile devices over a wireless multicast channel. The computing-enabled and caching-aided mobile devices are able to store the input or output datas of some tasks, and also compute some tasks locally, reducing the wireless bandwidth consumption. The corresponding framework of this system is established, and under the latency constraint, we jointly optimize the caching and computing policy at mobile devices to minimize the required transmission bandwidth. The joint policy optimization problem is shown to be NP-hard, and based on equivalent transformation and exact penalization of the problem, a stationary point is obtained via concave convex procedure (CCCP). Moreover, in a symmetric scenario, gains offered by this approach are derived to analytically understand the influences of caching and computing resources at mobile devices, multicast transmission, the number of mobile devices, as well as the number of tasks on the transmission bandwidth. Our results indicate that exploiting the computing and caching resources at mobile devices can provide significant bandwidth savings., to appear in IEEE GLOBECOM 2018

Multicast rate adaptation in WLAN has become a hot topic from the research community. However, wireless IP multicast lacks in feedback mechanism from the receiver and also no retransmission mechanism from packet loss. To achieve multicast reliability, multicast data is always transmitted at the basic data rate (e.g., 1Mbps for 802.11b). Moreover, wireless NDN multicast is essentially different from traditional wireless IP multicast. NDN multicast composition is based on Pending Interest Table (PIT) state information, which significantly increases the dynamics of the multicast groups. In this paper, we propose a multicast rate adaptation scheme to dynamically select the multicast transmission rate for NDN multicast communication. We present a mapping mechanism between the PIT entry and the MAC address of the station. To reduce the multicast transmission time, we propose a multi-rate multicast transmission scheme for the dynamic NDN multicast groups. In addition, we use the NDN caching mechanism to improve the reliability and reduce the transmission delay when the multicast data loss. Simulation results show that the proposed multicast rate adaptation scheme can effectively reduce transmission time while achieving lower delay and packet loss rate.

The forthcoming fifth generation (5G) networks are claimed to deliver the large amount of traffic generated by the huge number of heterogeneous devices that constitute the Internet of Things (IoT). This unprecedented volume of both human- and machine-generated traffic to be managed imposes 5G network operators to move the focus from throughput-optimized to energy-efficiency-optimized resource allocation solutions. Device-to-device (D2D) communications are recognized as an effective offloading technique that the 5G network can exploit to boost the capacity and energy efficiency of future 5G networks. In this paper, we design a technique to efficiently deliver multicast traffic in a 5G New Radio (NR) network by exploiting the benefits of D2D communication and single-frequency operation in order to improve the overall network energy efficiency. In the designed solution, the subset of devices in better channel conditions are served through a conventional multicast transmission, while cell-edge devices receive the multicast service from relay nodes that simultaneously transmit in D2D mode the same content. The dimension of the multicast serving area and the set of D2D connections to establish are chosen in order to maximize the overall network energy efficiency. Performed simulation results show the effectiveness of the proposed solution under varying frame configurations and number of multicast devices.

IP based satellite network will become an important component of Internet in the future. Due to the shared medium, it is more efficient to build transmission by using multicast than unicast. But how to run a reliable multicast in space Internet becomes a great challenge because satellite has limited resource to deal with massive feedback packages to ensure reliable transmission. Compared with ground Internet, the continuously dynamic topology of space Internet is also a big challenge to provide continuous multicast transmission. The terminals with multiple interface is more and more common, and terminals will have satellite access ability in future. How to make more efficient use of the advantages of satellite networks and terrestrial networks will become the focus of future research. In this paper, we extend current content delivery network architecture to support satellite networks at first. Then we propose a mechanism based on integrating multicast in satellite network and unicast using this architecture to take advantage of terrestrial and satellite networks. We use terrestrial network to aggregate the feedback information and retransmit loss packages to ensure reliable transmission in satellite multicast. We also propose a greedy algorithm and a zero-one linear programing model to select satellite when there are more than one satellites can connect with the terminal. We use STK to set up a simulation environment to evaluate our mechanism and algorithm. The result shows that the mechanism achieves efficient to reduce feedback information and the algorithm can balance handoff times and the numbers of selected satellite.

As a flexible network sharing mechanism, wireless network virtualization (WNV) can significantly improve the resource utilization and reduce the overall expense for the next generation wireless networks. Considering the users' common interests on popular contents, we introduce wireless multicast into wireless virtual networks. To serve the users who have requests on the same content via multicast transmission, both the virtual resources and content can be shared simultaneously. Thus, the virtual resources and backhaul bandwidth can be further released. In this paper, we propose a novel WNV based multicast system. Subsequently, the multicast group forming and sub-channel allocation strategies are jointly investigated in considered frameworks. Then we formulate the strategies as an integer nonlinear programming problem. Furthermore, we propose a heuristic algorithm with the aid of cutting-plane method to tackle the problem. Finally, Simulation results verify that our proposed scheme can significantly enhance the total utility of wireless virtual networks with lower backhaul usage and the proposed heuristic algorithm can achieve a perfect performance.

Date offloading is an efficient way to address the mobile traffic congestion by redirecting some traffic of a cellular network to complimentary networks. Meanwhile, multicast applications (e.g., video conference, IPTV, and the bulk software upgrade) are very popular. However, few of existing work investigates incentive mechanism design for multicast applications in mobile data offloading. In this paper, we focus on the multicast incentive mechanism design and propose a social-aware multicast incentive mechanism (SAMIM) for data offloading, where the cellular operator will offload the data of a multicast group to some WiFi access points (APs), then these APs serve mobile users (MUs) within their coverage area through multicast transmission. Numerical simulations demonstrate the good performance of SAMIM by comparing with IM-only. In specific, SAMIM improves the system social welfare by $20\%$ compared with IM-only with the number of selected APs $|\mathcal{W}| = 15$.

Multimedia applications and in particular video streaming and video conferencing over IEEE 802.11 wireless networks are becoming more and more common, such applications do not only require large bands but also impose strict QoS. Very High Throughput (VHT) amendments have permitted to boost data rates and provide larger bandwidth. However, this haven't resolve problems related to multicast transmission. Indeed, the IEEE 802.11aa amendment has been defined. The latter introduces new multicast transport policies, the Group Addressed Transmission Service (GATS), at the aim of ensuring a reliable multicast transport. In this paper we perform the first evaluation of the performance of the GATS in the context of an IEEE 802.11ac based network. Analysis show that the IEEE 802.11ac amendment have permitted to significantly enhance the performance of the aforementioned mechanisms. However, it raises problems related to reliability.

Ubiquitous connectivity in smart city and smart home scenarios gives rise to new uses cases for local distribution of data to multiple devices. In wireless local area networks, the common mode of data transport even for such scenarios is unicast, despite the broadcast nature of wireless medium. This is mainly due to lack of efficient mechanisms for high-throughput reliable multicast transmissions. In this paper we present an adaptive multicast rate control mechanism for IEEE 802.11 wireless networks, which can effectively improve the performance of multicast transfers while tolerating an adjustable level of packet loss at the MAC layer. Then we adapt and employ NORM as the transport layer protocol to complement the proposed multicast transmission rate control, as a proof of concept for cross-layer flexible handling of rate control and reliability. We compare the performance of this multicast approach to the common practice of TCP-based unicast data distribution as well as to the NORM-based multicast distribution at the basic transmission rate. The proposed approach is shown to scale well and improve data distribution performance for any given network topology and multicast receiver group size.