407 research outputs found
Rate-Splitting for Max-Min Fair Multigroup Multicast Beamforming in Overloaded Systems
In this paper, we consider the problem of achieving max-min fairness amongst
multiple co-channel multicast groups through transmit beamforming. We
explicitly focus on overloaded scenarios in which the number of transmitting
antennas is insufficient to neutralize all inter-group interference. Such
scenarios are becoming increasingly relevant in the light of growing
low-latency content delivery demands, and also commonly appear in multibeam
satellite systems. We derive performance limits of classical beamforming
strategies using DoF analysis unveiling their limitations; for example, rates
saturate in overloaded scenarios due to inter-group interference. To tackle
interference, we propose a strategy based on degraded beamforming and
successive interference cancellation. While the degraded strategy resolves the
rate-saturation issue, this comes at a price of sacrificing all spatial
multiplexing gains. This motivates the development of a unifying strategy that
combines the benefits of the two previous strategies. We propose a beamforming
strategy based on rate-splitting (RS) which divides the messages intended to
each group into a degraded part and a designated part, and transmits a
superposition of both degraded and designated beamformed streams. The
superiority of the proposed strategy is demonstrated through DoF analysis.
Finally, we solve the RS beamforming design problem and demonstrate significant
performance gains through simulations
Rank-Two Beamforming and Power Allocation in Multicasting Relay Networks
In this paper, we propose a novel single-group multicasting relay beamforming
scheme. We assume a source that transmits common messages via multiple
amplify-and-forward relays to multiple destinations. To increase the number of
degrees of freedom in the beamforming design, the relays process two received
signals jointly and transmit the Alamouti space-time block code over two
different beams. Furthermore, in contrast to the existing relay multicasting
scheme of the literature, we take into account the direct links from the source
to the destinations. We aim to maximize the lowest received quality-of-service
by choosing the proper relay weights and the ideal distribution of the power
resources in the network. To solve the corresponding optimization problem, we
propose an iterative algorithm which solves sequences of convex approximations
of the original non-convex optimization problem. Simulation results demonstrate
significant performance improvements of the proposed methods as compared with
the existing relay multicasting scheme of the literature and an algorithm based
on the popular semidefinite relaxation technique
A Rate-Splitting Strategy for Max-Min Fair Multigroup Multicasting
We consider the problem of transmit beamforming to multiple cochannel
multicast groups. The conventional approach is to beamform a designated data
stream to each group, while treating potential inter-group interference as
noise at the receivers. In overloaded systems where the number of transmit
antennas is insufficient to perform interference nulling, we show that
inter-group interference dominates at high SNRs, leading to a saturating
max-min fair performance. We propose a rather unconventional approach to cope
with this issue based on the concept of Rate-Splitting (RS). In particular,
part of the interference is broadcasted to all groups such that it is decoded
and canceled before the designated beams are decoded. We show that the RS
strategy achieves significant performance gains over the conventional
multigroup multicast beamforming strategy.Comment: accepted to the 17th IEEE International workshop on Signal Processing
advances in Wireless Communications (SPAWC 2016
Precoder Design for Physical Layer Multicasting
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.Comment: 37 pages, 8 figures, submitted to IEEE Trans. Signal Pro
Multicast Multigroup Beamforming for Per-antenna Power Constrained Large-scale Arrays
Large in the number of transmit elements, multi-antenna arrays with
per-element limitations are in the focus of the present work. In this context,
physical layer multigroup multicasting under per-antenna power constrains, is
investigated herein. To address this complex optimization problem
low-complexity alternatives to semi-definite relaxation are proposed. The goal
is to optimize the per-antenna power constrained transmitter in a maximum
fairness sense, which is formulated as a non-convex quadratically constrained
quadratic problem. Therefore, the recently developed tool of feasible point
pursuit and successive convex approximation is extended to account for
practical per-antenna power constraints. Interestingly, the novel iterative
method exhibits not only superior performance in terms of approaching the
relaxed upper bound but also a significant complexity reduction, as the
dimensions of the optimization variables increase. Consequently, multicast
multigroup beamforming for large-scale array transmitters with per-antenna
dedicated amplifiers is rendered computationally efficient and accurate. A
preliminary performance evaluation in large-scale systems for which the
semi-definite relaxation constantly yields non rank-1 solutions is presented.Comment: submitted to IEEE SPAWC 2015. arXiv admin note: substantial text
overlap with arXiv:1406.755
Coordinated Multicast Beamforming in Multicell Networks
We study physical layer multicasting in multicell networks where each base
station, equipped with multiple antennas, transmits a common message using a
single beamformer to multiple users in the same cell. We investigate two
coordinated beamforming designs: the quality-of-service (QoS) beamforming and
the max-min SINR (signal-to-interference-plus-noise ratio) beamforming. The
goal of the QoS beamforming is to minimize the total power consumption while
guaranteeing that received SINR at each user is above a predetermined
threshold. We present a necessary condition for the optimization problem to be
feasible. Then, based on the decomposition theory, we propose a novel
decentralized algorithm to implement the coordinated beamforming with limited
information sharing among different base stations. The algorithm is guaranteed
to converge and in most cases it converges to the optimal solution. The max-min
SINR (MMS) beamforming is to maximize the minimum received SINR among all users
under per-base station power constraints. We show that the MMS problem and a
weighted peak-power minimization (WPPM) problem are inverse problems. Based on
this inversion relationship, we then propose an efficient algorithm to solve
the MMS problem in an approximate manner. Simulation results demonstrate
significant advantages of the proposed multicast beamforming algorithms over
conventional multicasting schemes.Comment: 10pages, 9 figure
Waveform Design for Secure SISO Transmissions and Multicasting
Wireless physical-layer security is an emerging field of research aiming at
preventing eavesdropping in an open wireless medium. In this paper, we propose
a novel waveform design approach to minimize the likelihood that a message
transmitted between trusted single-antenna nodes is intercepted by an
eavesdropper. In particular, with knowledge first of the eavesdropper's channel
state information (CSI), we find the optimum waveform and transmit energy that
minimize the signal-to-interference-plus-noise ratio (SINR) at the output of
the eavesdropper's maximum-SINR linear filter, while at the same time provide
the intended receiver with a required pre-specified SINR at the output of its
own max-SINR filter. Next, if prior knowledge of the eavesdropper's CSI is
unavailable, we design a waveform that maximizes the amount of energy available
for generating disturbance to eavesdroppers, termed artificial noise (AN),
while the SINR of the intended receiver is maintained at the pre-specified
level. The extensions of the secure waveform design problem to multiple
intended receivers are also investigated and semidefinite relaxation (SDR) -an
approximation technique based on convex optimization- is utilized to solve the
arising NP-hard design problems. Extensive simulation studies confirm our
analytical performance predictions and illustrate the benefits of the designed
waveforms on securing single-input single-output (SISO) transmissions and
multicasting
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