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Jeffrey G Andrews - One of the best experts on this subject based on the ideXlab platform.
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Multicast outage probability and Transmission capacity of multihop wireless networks
IEEE Transactions on Information Theory, 2011Co-Authors: Chunhung Liu, Jeffrey G AndrewsAbstract:Multicast Transmission, wherein the same packet must be delivered to multiple receivers, is an important aspect of sensor and tactical networks and has several distinctive traits as opposed to more commonly studied unicast networks. Specially, these include 1) identical packets must be delivered successfully to several nodes, 2) outage at any receiver requires the packet to be retransmitted at least to that receiver, and 3) the Multicast rate is dominated by the receiver with the weakest link in order to minimize outage and reTransmission. A first contribution of this paper is the development of a tractable Multicast model and throughput metric that captures each of these key traits in a Multicast wireless network. We utilize a Poisson cluster process (PCP) consisting of a distinct Poisson point process (PPP) for the transmitters and receivers, and then define the Multicast Transmission capacity (MTC) as the maximum achievable Multicast rate per Transmission attempt times the maximum intensity of Multicast clusters under decoding delay and Multicast outage constraints. A Multicast cluster is a contiguous area over which a packet is Multicasted, and to reduce outage it can be tessellated into v smaller regions of Multicast. The second contribution of the paper is the analysis of several key aspects of this model, for which we develop the following main result. Assuming τ/v Transmission attempts are allowed for each tessellated region in a Multicast cluster, we show that the MTC is Θ(ρkxlog(k)vy) where ρ, x and y are functions of τ and v depending on the network size and intensity, and k is the average number of the intended receivers in a cluster. We derive {ρ, x, y} for a number of regimes of interest, and also show that an appropriate number of reTransmissions can significantly enhance the MTC.
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Multicast capacity scaling of wireless networks with Multicast outage
International Symposium on Information Theory, 2010Co-Authors: Chunhung Liu, Jeffrey G AndrewsAbstract:Multicast Transmission has several distinctive traits as opposed to more commonly studied unicast networks. Specially, these include (i) identical packets must be delivered successfully to several nodes, (ii) outage could simultaneously happen at different receivers, and (iii) the Multicast rate is dominated by the receiver with the weakest link in order to minimize outage and reTransmission. To capture these key traits, we utilize a Poisson cluster process consisting of a distinct Poisson point process (PPP) for the transmitters and receivers, and then define the Multicast Transmission capacity (MTC) as the maximum achievable Multicast rate times the number of Multicast clusters per unit volume, accounting for outages and reTransmissions. Our main result shows that if τ Transmission attempts are allowed in a Multicast cluster, the MTC is Θ(ρkx log(k)) where ρ and x are functions of τ depending on the network size and density, and k is the average number of the intended receivers in a cluster. We also show that an appropriate number of reTransmissions can significantly enhance the MTC.
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Multicast capacity scaling of wireless networks with Multicast outage
arXiv: Information Theory, 2010Co-Authors: Chunhung Liu, Jeffrey G AndrewsAbstract:Multicast Transmission has several distinctive traits as opposed to more commonly studied unicast networks. Specially, these include (i) identical packets must be delivered successfully to several nodes, (ii) outage could simultaneously happen at different receivers, and (iii) the Multicast rate is dominated by the receiver with the weakest link in order to minimize outage and reTransmission. To capture these key traits, we utilize a Poisson cluster process consisting of a distinct Poisson point process (PPP) for the transmitters and receivers, and then define the Multicast Transmission capacity (MTC) as the maximum achievable Multicast rate times the number of Multicast clusters per unit volume, accounting for outages and reTransmissions. Our main result shows that if $\tau$ Transmission attempts are allowed in a Multicast cluster, the MTC is $\Theta\left(\rho k^{x}\log(k)\right)$ where $\rho$ and $x$ are functions of $\tau$ depending on the network size and density, and $k$ is the average number of the intended receivers in a cluster. We also show that an appropriate number of reTransmissions can significantly enhance the MTC.
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Multicast outage probability and Transmission capacity of multihop wireless networks
arXiv: Information Theory, 2010Co-Authors: Chunhung Liu, Jeffrey G AndrewsAbstract:Multicast Transmission, wherein the same packet must be delivered to multiple receivers, is an important aspect of sensor and tactical networks and has several distinctive traits as opposed to more commonly studied unicast networks. Specially, these include (i) identical packets must be delivered successfully to several nodes, (ii) outage at any receiver requires the packet to be retransmitted at least to that receiver, and (iii) the Multicast rate is dominated by the receiver with the weakest link in order to minimize outage and reTransmission. A first contribution of this paper is the development of a tractable Multicast model and throughput metric that captures each of these key traits in a Multicast wireless network. We utilize a Poisson cluster process (PCP) consisting of a distinct Poisson point process (PPP) for the transmitters and receivers, and then define the Multicast Transmission capacity (MTC) as the maximum achievable Multicast rate per Transmission attempt times the maximum intensity of Multicast clusters under decoding delay and Multicast outage constraints. A Multicast cluster is a contiguous area over which a packet is Multicasted, and to reduce outage it can be tessellated into $v$ smaller regions of Multicast. The second contribution of the paper is the analysis of several key aspects of this model, for which we develop the following main result. Assuming $\tau/v$ Transmission attempts are allowed for each tessellated region in a Multicast cluster, we show that the MTC is $\Theta(\rho k^{x}\log(k)v^{y})$ where $\rho$, $x$ and $y$ are functions of $\tau$ and $v$ depending on the network size and intensity, and $k$ is the average number of the intended receivers in a cluster. We derive $\{\rho, x, y\}$ for a number of regimes of interest, and also show that an appropriate number of reTransmissions can significantly enhance the MTC.
Chunhung Liu - One of the best experts on this subject based on the ideXlab platform.
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on the impact of delay constraint on the Multicast outage in wireless fading environment
International Conference on Communications, 2015Co-Authors: Mohammad G Khoshkholgh, Keivan Navaie, Kang G Shin, Chunhung Liu, Yan Zhang, Victor Leung, Stein GjessingAbstract:In this paper we investigate single-hop Multicast Transmission in which randomly located multiple transmitters Multicast packets to a cluster of receivers. Packet reTransmission is known as a promising mechanism for improving the Transmission reliability. Our focus is on evaluating (i) the minimum required delay (reTransmission attempts), τ*, for establishing an outage-free Multicast, where a transmitted packet is successfully decoded by entire nodes in the cluster, and (ii) Multicast Progress Radius (MPR) for a given delay constraint. MPR indicates how far, on average, a packet can successfully progress in a cluster without outage while the reTransmission delay is restricted. Assuming general fading distribution, we derive closed-form expressions for the cumulative distribution function of τ*, and MPR. By simulations we confirmed our analysis and studied the impact of several system parameters on the MPR. Based on results of this paper we conclude that outage-free Multicast requires a very large number of reTransmission attempts, thus not practically achievable only based on reTransmission.
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Multicast outage probability and Transmission capacity of multihop wireless networks
IEEE Transactions on Information Theory, 2011Co-Authors: Chunhung Liu, Jeffrey G AndrewsAbstract:Multicast Transmission, wherein the same packet must be delivered to multiple receivers, is an important aspect of sensor and tactical networks and has several distinctive traits as opposed to more commonly studied unicast networks. Specially, these include 1) identical packets must be delivered successfully to several nodes, 2) outage at any receiver requires the packet to be retransmitted at least to that receiver, and 3) the Multicast rate is dominated by the receiver with the weakest link in order to minimize outage and reTransmission. A first contribution of this paper is the development of a tractable Multicast model and throughput metric that captures each of these key traits in a Multicast wireless network. We utilize a Poisson cluster process (PCP) consisting of a distinct Poisson point process (PPP) for the transmitters and receivers, and then define the Multicast Transmission capacity (MTC) as the maximum achievable Multicast rate per Transmission attempt times the maximum intensity of Multicast clusters under decoding delay and Multicast outage constraints. A Multicast cluster is a contiguous area over which a packet is Multicasted, and to reduce outage it can be tessellated into v smaller regions of Multicast. The second contribution of the paper is the analysis of several key aspects of this model, for which we develop the following main result. Assuming τ/v Transmission attempts are allowed for each tessellated region in a Multicast cluster, we show that the MTC is Θ(ρkxlog(k)vy) where ρ, x and y are functions of τ and v depending on the network size and intensity, and k is the average number of the intended receivers in a cluster. We derive {ρ, x, y} for a number of regimes of interest, and also show that an appropriate number of reTransmissions can significantly enhance the MTC.
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Multicast capacity scaling of wireless networks with Multicast outage
International Symposium on Information Theory, 2010Co-Authors: Chunhung Liu, Jeffrey G AndrewsAbstract:Multicast Transmission has several distinctive traits as opposed to more commonly studied unicast networks. Specially, these include (i) identical packets must be delivered successfully to several nodes, (ii) outage could simultaneously happen at different receivers, and (iii) the Multicast rate is dominated by the receiver with the weakest link in order to minimize outage and reTransmission. To capture these key traits, we utilize a Poisson cluster process consisting of a distinct Poisson point process (PPP) for the transmitters and receivers, and then define the Multicast Transmission capacity (MTC) as the maximum achievable Multicast rate times the number of Multicast clusters per unit volume, accounting for outages and reTransmissions. Our main result shows that if τ Transmission attempts are allowed in a Multicast cluster, the MTC is Θ(ρkx log(k)) where ρ and x are functions of τ depending on the network size and density, and k is the average number of the intended receivers in a cluster. We also show that an appropriate number of reTransmissions can significantly enhance the MTC.
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Multicast capacity scaling of wireless networks with Multicast outage
arXiv: Information Theory, 2010Co-Authors: Chunhung Liu, Jeffrey G AndrewsAbstract:Multicast Transmission has several distinctive traits as opposed to more commonly studied unicast networks. Specially, these include (i) identical packets must be delivered successfully to several nodes, (ii) outage could simultaneously happen at different receivers, and (iii) the Multicast rate is dominated by the receiver with the weakest link in order to minimize outage and reTransmission. To capture these key traits, we utilize a Poisson cluster process consisting of a distinct Poisson point process (PPP) for the transmitters and receivers, and then define the Multicast Transmission capacity (MTC) as the maximum achievable Multicast rate times the number of Multicast clusters per unit volume, accounting for outages and reTransmissions. Our main result shows that if $\tau$ Transmission attempts are allowed in a Multicast cluster, the MTC is $\Theta\left(\rho k^{x}\log(k)\right)$ where $\rho$ and $x$ are functions of $\tau$ depending on the network size and density, and $k$ is the average number of the intended receivers in a cluster. We also show that an appropriate number of reTransmissions can significantly enhance the MTC.
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Multicast outage probability and Transmission capacity of multihop wireless networks
arXiv: Information Theory, 2010Co-Authors: Chunhung Liu, Jeffrey G AndrewsAbstract:Multicast Transmission, wherein the same packet must be delivered to multiple receivers, is an important aspect of sensor and tactical networks and has several distinctive traits as opposed to more commonly studied unicast networks. Specially, these include (i) identical packets must be delivered successfully to several nodes, (ii) outage at any receiver requires the packet to be retransmitted at least to that receiver, and (iii) the Multicast rate is dominated by the receiver with the weakest link in order to minimize outage and reTransmission. A first contribution of this paper is the development of a tractable Multicast model and throughput metric that captures each of these key traits in a Multicast wireless network. We utilize a Poisson cluster process (PCP) consisting of a distinct Poisson point process (PPP) for the transmitters and receivers, and then define the Multicast Transmission capacity (MTC) as the maximum achievable Multicast rate per Transmission attempt times the maximum intensity of Multicast clusters under decoding delay and Multicast outage constraints. A Multicast cluster is a contiguous area over which a packet is Multicasted, and to reduce outage it can be tessellated into $v$ smaller regions of Multicast. The second contribution of the paper is the analysis of several key aspects of this model, for which we develop the following main result. Assuming $\tau/v$ Transmission attempts are allowed for each tessellated region in a Multicast cluster, we show that the MTC is $\Theta(\rho k^{x}\log(k)v^{y})$ where $\rho$, $x$ and $y$ are functions of $\tau$ and $v$ depending on the network size and intensity, and $k$ is the average number of the intended receivers in a cluster. We derive $\{\rho, x, y\}$ for a number of regimes of interest, and also show that an appropriate number of reTransmissions can significantly enhance the MTC.
Bruno Clerckx - One of the best experts on this subject based on the ideXlab platform.
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Rate-Splitting Multiple Access for Multigroup Multicast Cellular and Satellite Communications: PHY Layer Design and Link-Level Simulations.
arXiv: Information Theory, 2021Co-Authors: Longfei Yin, Onur Dizdar, Bruno ClerckxAbstract:Rate-splitting multiple access (RSMA), relying on linearly precoded rate-splitting (RS) at the transmitter and successive interference cancellation (SIC) at the receivers has emerged as a powerful and flexible multiple access strategy for downlink multi-user multi-antenna systems. Through message splitting and the Transmission of both common and private messages, RSMA has been demonstrated to be a robust interference management strategy which enables partially decoding interference and partially treating interference as noise. In this work, we consider the application of RSMA in a multigroup Multicast scenario, where each message is intended to a group of users. By leveraging the recent results on the max-min fair (MMF) optimization problem of RSMA-based multigroup Multicast beamforming with imperfect channel state information at the transmitter (CSIT), we investigate the design of the physical (PHY) layer including finite length polar coding, finite alphabet modulation, adaptive modulation and coding (AMC) algorithm, and SIC receivers, etc. Link-level simulation (LLS) results verify the superiority of RSMA-based multigroup Multicast Transmission compared with space-division multiple access (SDMA)-based strategy in both cellular systems and multibeam satellite systems.
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dirty paper coded rate splitting for non orthogonal unicast and Multicast Transmission with partial csit
Asilomar Conference on Signals Systems and Computers, 2020Co-Authors: Yijie Mao, Bruno ClerckxAbstract:A Non-Orthogonal Unicast and Multicast (NOUM) Transmission system allows a Multicast stream intended to all receivers to be jointly transmitted with unicast streams in the same time-frequency resource blocks. While the capacity of the two-user multi-antenna NOUM with perfect Channel State Information at the Transmitter (CSIT) is known and achieved by Dirty Paper Coding (DPC)-assisted NOUM with Superposition Coding (SC), the capacity and the capacity-achieving strategy of the multi-antenna NOUM with partial CSIT remain unknown. In this work, we focus on the partial CSIT setting and make two major contributions. First, we show that linearly precoded Rate-Splitting (RS), relying on splitting unicast messages into common and private parts, encoding the common parts together with the Multicast message and linearly precoding at the transmitter, can achieve larger rate regions than DPC-assisted NOUM with partial CSIT. Second, we study Dirty Paper Coded Rate-Splitting (DPCRS), that marries RS and DPC. We show that the rate region of DPCRS-assisted NOUM is enlarged beyond that of conventional DPC-assisted NOUM and that of linearly precoded RS-assisted NOUM with partial CSIT.
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rate splitting for multi antenna non orthogonal unicast and Multicast Transmission spectral and energy efficiency analysis
IEEE Transactions on Communications, 2019Co-Authors: Yijie Mao, Bruno ClerckxAbstract:In a Non-Orthogonal Unicast and Multicast (NOUM) Transmission system, a Multicast stream intended to all the receivers is superimposed in the power domain on the unicast streams. One layer of Successive Interference Cancellation (SIC) is required at each receiver to remove the Multicast stream before decoding its intended unicast stream. In this paper, we first show that a linearly-precoded 1-layer Rate-Splitting (RS) strategy at the transmitter can efficiently exploit this existing SIC receiver architecture. By splitting the unicast messages into common and private parts and encoding the common parts along with the Multicast message into a super-common stream decoded by all users, the SIC is better reused for the dual purpose of separating the unicast and Multicast streams as well as better managing the multi-user interference among the unicast streams. We further propose multi-layer Transmission strategies based on the generalized RS and power-domain Non-Orthogonal Multiple Access (NOMA). Two different objectives are studied for the design of the precoders, namely, maximizing the Weighted Sum Rate (WSR) of the unicast messages and maximizing the system Energy Efficiency (EE), both subject to Quality of Service (QoS) rate requirements of all messages and a sum power constraint. A Weighted Minimum Mean Square Error (WMMSE)-based algorithm and a Successive Convex Approximation (SCA)-based algorithm are proposed to solve the WSR and EE problems, respectively. Numerical results show that the proposed RS-assisted NOUM Transmission strategies are more spectrally and energy efficient than the conventional Multi-User Linear-Precoding (MU–LP), Orthogonal Multiple Access (OMA) and power-domain NOMA in a wide range of user deployments (with a diversity of channel directions, channel strengths and qualities of channel state information at the transmitter) and network loads (underloaded and overloaded regimes). It is superior for the downlink multi-antenna NOUM Transmission.
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rate splitting for multi antenna non orthogonal unicast and Multicast Transmission spectral and energy efficiency analysis
arXiv: Information Theory, 2018Co-Authors: Yijie Mao, Bruno ClerckxAbstract:In a Non-Orthogonal Unicast and Multicast (NOUM) Transmission system, a Multicast stream intended to all the receivers is superimposed in the power domain on the unicast streams. One layer of Successive Interference Cancellation (SIC) is required at each receiver to remove the Multicast stream before decoding its intended unicast stream. In this paper, we first show that a linearly-precoded 1-layer Rate-Splitting (RS) strategy at the transmitter can efficiently exploit this existing SIC receiver architecture. We further propose multi-layer Transmission strategies based on the generalized RS and power-domain Non-Orthogonal Multiple Access (NOMA). Two different objectives are studied for the design of the precoders, namely, maximizing the Weighted Sum Rate (WSR) of the unicast messages and maximizing the system Energy Efficiency (EE), both subject to Quality of Service (QoS) rate requirements of all the messages and a sum power constraint. A Weighted Minimum Mean Square Error (WMMSE)-based algorithm and a Successive Convex Approximation (SCA)-based algorithm are proposed to solve the WSR and EE problems, respectively. Numerical results show that the proposed RS-assisted NOUM Transmission strategies are more spectrally and energy efficient than the conventional Multi-User Linear-Precoding (MU-LP), Orthogonal Multiple Access (OMA) and power-domain NOMA in a wide range of user deployments (with a diversity of channel directions, channel strengths and qualities of channel state information at the transmitter) and network loads (underloaded and overloaded regimes). It is superior for the downlink multi-antenna NOUM Transmission.
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rate splitting for multi antenna non orthogonal unicast and Multicast Transmission
International Workshop on Signal Processing Advances in Wireless Communications, 2018Co-Authors: Yijie Mao, Bruno ClerckxAbstract:In a superimposed unicast and Multicast Transmission system, one layer of Successive Interference Cancellation (SIC) is required at each receiver to remove the Multicast stream before decoding the unicast stream. In this paper, we show that a linearly-precoded Rate-Splitting (RS) strategy at the transmitter can efficiently exploit this existing SIC receiver architecture. By splitting the unicast messages into common and private parts and encoding the common parts along with the Multicast message into a super-common stream decoded by all users, the SIC is used for the dual purpose of separating the unicast and Multicast streams as well as better managing the multi-user interference between the unicast streams. The precoders are designed with the objective of maximizing the Weighted Sum Rate (WSR) of the unicast messages subject to a Quality of Service (QoS) requirement of the Multicast message and a sum power constraint. Numerical results show that RS outperforms existing Multi-User Linear-Precoding (MU-LP) and power-domain Non-Orthogonal Multiple Access (NOMA) in a wide range of user deployments (with a diversity of channel directions and channel strengths). Moreover, since one layer of SIC is required to separate the unicast and Multicast streams, the performance gain of RS comes without any increase in the receiver complexity compared with MU-LP. Hence, in such non-orthogonal unicast and Multicast Transmissions, RS provides rate and QoS enhancements at no extra cost for the receivers.
Chunhsin Wang - One of the best experts on this subject based on the ideXlab platform.
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in single hop wdm networks a data packet can be transmitted from one node to another only when one of the transmitters of the source node and one of the receivers of the destination node are tuned to the same wavelength i e a data packet is transmitted from one node to another without going through intermediate nodes a hybrid Multicast scheduling algorithm for single hop wdm networks
Journal of Lightwave Technology, 2001Co-Authors: Hwachun Lin, Chunhsin WangAbstract:This paper shows that, for single-hop wavelength division multiplexing (WDM) networks, a Multicast scheduling algorithm which always tries to partition a Multicast Transmission into multiple unicast or Multicast Transmissions may not always produce lower mean packet delay than a Multicast scheduling algorithm that does not partition Multicast Transmissions. The performance of a Multicast scheduling algorithm may depend on the traffic conditions and the availability of the channel resource in the network. A hybrid Multicast scheduling algorithm that can be used in single-hop WDM networks.
Wolfgang Kellerer - One of the best experts on this subject based on the ideXlab platform.
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energy efficient analog beamformer design for mmwave Multicast Transmission
IEEE Transactions on Green Communications and Networking, 2019Co-Authors: Zihuan Wang, Qian Liu, Wolfgang KellererAbstract:Millimeter wave (mmWave) communication is considered as a key enabling technology for 5G cellular networks because abundant spectrum in mmWave bands can provide multi-gigabit communication service. Analog beamforming architecture, which employs energy-efficient phase shifters (PSs) instead of energy-hungry radio frequency (RF) components, has emerged as a promising solution to overcome severe propagation loss of mmWave channels. On the other hand, Multicast communication is another efficient approach to address the dramatic traffic demand by utilizing the broadcast nature of the wireless medium. This paper investigates energy efficient analog beamforming in mmWave single-group Multicast communication systems. We focus on max–min fair (MMF) problem and aim to design the analog beamformer to maximize the minimum signal-to-noise ratio (SNR) over all users subject to a transmit power constraint. The analog beamformer design with infinite and finite resolution PSs are both studied. While the constraints of PSs make the problem intractable, we propose an alternative low-complexity algorithm, which iteratively determines each element of analog beamformer. Furthermore, we also investigate the asymptotically optimal beamformer designs and provide asymptotic performance analysis for large-scale mmWave Multicasting systems. Extensive simulation results illustrate the effectiveness of the proposed analog beamforming designs in mmWave Multicast systems. Besides, numerical results also demonstrate that the asymptotic performance of the proposed scheme is close to the optimal case.
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efficient analog beamforming for max min fair Multicast Transmission
Vehicular Technology Conference, 2019Co-Authors: Zihuan Wang, Wolfgang KellererAbstract:This paper investigates analog beamforming with large-scale antenna arrays for single-group Multicast Transmission. We focus on the max-min fair (MMF) problem and aim to design the analog beamformer with infinite and finite resolution phase shifters (PSs), respectively, to maximize the minimum signal-to-noise ratio (SNR) over all users subject to a transmit power constraint. However, the constant magnitude and infinite/finite phase constraints imposed by PSs frustrate the access of an optimal solution of analog beamformer. We thus formulate a sub-optimal MMF problem alternatively and propose a low- complexity algorithm, which iteratively determines each element of analog beamformer to conditionally maximize the minimum SNR among users. The computational complexities of our proposed algorithms are linear in the number of antennas. Simulation results illustrate that our proposed analog beamformer design can achieve satisfactory performance which is close to the full-digital case and outperform the other state- of-the-art schemes.