Beamforming for physical layer multicasting

Senaratne, Damith; Tellambura, Chintha

doi:10.1109/wcnc.2011.5779431

Cited by 13 publications

(11 citation statements)

References 15 publications

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“…While the works in [4]- [14] investigated multicasting systems with single-antenna receivers, recently multi-antenna receivers have been considered [15]- [17] for multicasting systems since receiver beamforming can significantly improve the system performance. In particular, coordinated beamforming techniques have been investigated in [15], where a generalized form of block diagonalization has been proposed to make orthogonal transmissions to distinct multicasting groups with multi-antenna receivers.…”

Section: Introductionmentioning

confidence: 99%

“…In particular, coordinated beamforming techniques have been investigated in [15], where a generalized form of block diagonalization has been proposed to make orthogonal transmissions to distinct multicasting groups with multi-antenna receivers. The scaling of the achievable rate with increasing number of users was investigated in [16] for multiple-input multiple-output (MIMO) multicasting where the transmission is coded at the application layer over a number of channel realizations.…”

Section: Introductionmentioning

confidence: 99%

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Transceiver Optimization for Multi-Hop MIMO Relay Multicasting From Multiple Sources

Khandaker¹,

Rong

2014

IEEE Trans. Wireless Commun.

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In this paper, we consider a multicasting multipleinput multiple-output (MIMO) relay system where multiple transmitters multicast their own messages to a group of receivers over multiple hops, and all nodes are equipped with multiple antennas. The joint transmit and relay precoding design problem has been investigated for multicasting multiple data streams based on min-max mean-squared error (MSE) criterion. We aim at minimizing the maximal MSE of the signal waveform estimation among all receivers subjecting to power constraints at the transmitters and all the relay nodes. This problem is highly nonconvex with matrix variables and the exactly optimal solution is very hard to obtain. We develop an iterative algorithm to jointly optimize the transmitter, relay, and receiver matrices by solving convex subproblems. By exploiting the optimal structure of the relay precoding matrices, we then propose a low complexity solution for the problem under some mild approximation. In particular, we show that under (moderately) high signal-to-noise ratio assumption, the min-max optimization problem can be solved using the semidefinite programming technique. Numerical simulations demonstrate the effectiveness of the proposed algorithms.

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Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Transceiver Optimization for Multi-Hop MIMO Relay Multicasting From Multiple Sources

Khandaker¹,

Rong

2014

IEEE Trans. Wireless Commun.

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“…The works in [4]- [5] solved the max-min signal-to-interference-plus-noise ratio (SINR)/rate beamforming problems with the aid of semidefinite relaxations (SDR). In [6], a stochastic beam forming strategy is proposed for multi-antenna physical-layer multicasting considering an achievable rate perspective where [7] focus on multicasting systems with single-antenna receiving nodes, recently multi-antenna receiving nodes have been considered in [8]- [10]. In particular, coordinated beamforming techniques have been investigated in [8] to facilitate physical layer multicasting with multi antenna receivers.…”

Section: Introductionmentioning

confidence: 99%

“…In [6], a stochastic beam forming strategy is proposed for multi-antenna physical-layer multicasting considering an achievable rate perspective where [7] focus on multicasting systems with single-antenna receiving nodes, recently multi-antenna receiving nodes have been considered in [8]- [10]. In particular, coordinated beamforming techniques have been investigated in [8] to facilitate physical layer multicasting with multi antenna receivers. In [9], non-iterative near-optimal transmit beamformers are designed for wireless link layer multicasting with real-valued channels, and for complex-valued channels an upper bound on the multicasting rate is derived.…”

Section: Introductionmentioning

confidence: 99%

Multicasting MIMO relay optimization based on min-max MSE criterion

Khandaker

Rong

2012

2012 IEEE International Conference on Communication Systems (ICCS)

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In this paper, we consider a multicasting multiple input multiple-output (MIMO) relay system where the transmit ter multi casts a common message to multiple receivers with the aid of a relay node, all equipped with multiple antennas. Given the power constraints at the source and the relay nodes, we aim at minimizing the maximal mean-squared error (MSE) of the signal waveform estimation among the destination nodes through joint source, relay, and receiver matrices optimization. We provide a low complexity solution to this highly nonconvex optimization problem. In particular, we show that under the (moderately) high signal-to-noise ratio (SNR) assumption, the joint source and relay optimization problem can be solved using standard semidefinite programming (SDP) technique. Numerical simulations provided demonstrate the effectiveness of the proposed algorithm.

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“…Several efficient heuristics are suggested. This approach is further pursued in [11], where formation of groups is also considered and transmissions pertaining to different groups are made orthogonal. Long-term beamforming for scenarios where instantaneous channel state is unavailable at the transmitter has been addressed in [5].…”

Section: Introductionmentioning

confidence: 99%

Precoder Design for Physical Layer Multicasting

Zhu

Prasad²,

Rangarajan³

2012

IEEE Trans. Signal Process.

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This paper studies the instantaneous rate maximization and the weighted sum delay minimization problems over a K-user multicast channel, where multiple antennas are available at the transmitter as well as at all the receivers. Motivated by the degree of freedom optimality and the simplicity offered by linear precoding schemes, we consider the design of linear precoders using the aforementioned two criteria.We first consider the scenario wherein the linear precoder can be any complex-valued matrix subject to rank and power constraints. We propose cyclic alternating ascent based precoder design algorithms and establish their convergence to respective stationary points. Simulation results reveal that our proposed algorithms considerably outperform known competing solutions. We then consider a scenario in which the linear precoder can be formed by selecting and concatenating precoders from a given finite codebook of precoding matrices, subject to rank and power constraints. We show that under this scenario, the instantaneous rate maximization problem is equivalent to a robust submodular maximization problem which is strongly NP hard. We propose a deterministic approximation algorithm and show that it yields a bicriteria approximation. For the weighted sum delay minimization problem we propose a simple deterministic greedy algorithm, which at each step entails approximately maximizing a submodular set function subject to multiple knapsack constraints, and establish its performance guarantee.

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Beamforming for physical layer multicasting

Cited by 13 publications

References 15 publications

Transceiver Optimization for Multi-Hop MIMO Relay Multicasting From Multiple Sources

Transceiver Optimization for Multi-Hop MIMO Relay Multicasting From Multiple Sources

Multicasting MIMO relay optimization based on min-max MSE criterion

Precoder Design for Physical Layer Multicasting

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