458 research outputs found
Generic Multiuser Coordinated Beamforming for Underlay Spectrum Sharing
The beamforming techniques have been recently studied as possible enablers
for underlay spectrum sharing. The existing beamforming techniques have several
common limitations: they are usually system model specific, cannot operate with
arbitrary number of transmit/receive antennas, and cannot serve arbitrary
number of users. Moreover, the beamforming techniques for underlay spectrum
sharing do not consider the interference originating from the incumbent primary
system. This work extends the common underlay sharing model by incorporating
the interference originating from the incumbent system into generic combined
beamforming design that can be applied on interference, broadcast or multiple
access channels. The paper proposes two novel multiuser beamforming algorithms
for user fairness and sum rate maximization, utilizing newly derived convex
optimization problems for transmit and receive beamformers calculation in a
recursive optimization. Both beamforming algorithms provide efficient operation
for the interference, broadcast and multiple access channels, as well as for
arbitrary number of antennas and secondary users in the system. Furthermore,
the paper proposes a successive transmit/receive optimization approach that
reduces the computational complexity of the proposed recursive algorithms. The
results show that the proposed complexity reduction significantly improves the
convergence rates and can facilitate their operation in scenarios which require
agile beamformers computation.Comment: 30 pages, 5 figure
Spectrum Sharing in Wireless Networks via QoS-Aware Secondary Multicast Beamforming
Secondary spectrum usage has the potential to considerably increase spectrum utilization. In this paper, quality-of-service (QoS)-aware spectrum underlay of a secondary multicast network is considered. A multiantenna secondary access point (AP) is used for multicast (common information) transmission to a number of secondary single-antenna receivers. The idea is that beamforming can be used to steer power towards the secondary receivers while limiting sidelobes that cause interference to primary receivers. Various optimal formulations of beamforming are proposed, motivated by different ldquocohabitationrdquo scenarios, including robust designs that are applicable with inaccurate or limited channel state information at the secondary AP. These formulations are NP-hard computational problems; yet it is shown how convex approximation-based multicast beamforming tools (originally developed without regard to primary interference constraints) can be adapted to work in a spectrum underlay context. Extensive simulation results demonstrate the effectiveness of the proposed approaches and provide insights on the tradeoffs between different design criteria
Cognitive Beamforming for Multiple Secondary Data Streams With Individual SNR Constraints
In this paper, we consider cognitive beamforming for multiple secondary data
streams subject to individual signal-to-noise ratio (SNR) requirements for each
secondary data stream. In such a cognitive radio system, the secondary user is
permitted to use the spectrum allocated to the primary user as long as the
caused interference at the primary receiver is tolerable. With both secondary
SNR constraint and primary interference power constraint, we aim to minimize
the secondary transmit power consumption. By exploiting the individual SNR
requirements, we formulate this cognitive beamforming problem as an
optimization problem on the Stiefel manifold. Both zero forcing beamforming
(ZFB) and nonzero forcing beamforming (NFB) are considered. For the ZFB case,
we derive a closed form beamforming solution. For the NFB case, we prove that
the strong duality holds for the nonconvex primal problem and thus the optimal
solution can be easily obtained by solving the dual problem. Finally, numerical
results are presented to illustrate the performance of the proposed cognitive
beamforming solutions.Comment: This is the longer version of a paper to appear in the IEEE
Transactions on Signal Processin
Beamforming Techniques for Non-Orthogonal Multiple Access in 5G Cellular Networks
In this paper, we develop various beamforming techniques for downlink
transmission for multiple-input single-output (MISO) non-orthogonal multiple
access (NOMA) systems. First, a beamforming approach with perfect channel state
information (CSI) is investigated to provide the required quality of service
(QoS) for all users. Taylor series approximation and semidefinite relaxation
(SDR) techniques are employed to reformulate the original non-convex power
minimization problem to a tractable one. Further, a fairness-based beamforming
approach is proposed through a max-min formulation to maintain fairness between
users. Next, we consider a robust scheme by incorporating channel
uncertainties, where the transmit power is minimized while satisfying the
outage probability requirement at each user. Through exploiting the SDR
approach, the original non-convex problem is reformulated in a linear matrix
inequality (LMI) form to obtain the optimal solution. Numerical results
demonstrate that the robust scheme can achieve better performance compared to
the non-robust scheme in terms of the rate satisfaction ratio. Further,
simulation results confirm that NOMA consumes a little over half transmit power
needed by OMA for the same data rate requirements. Hence, NOMA has the
potential to significantly improve the system performance in terms of transmit
power consumption in future 5G networks and beyond.Comment: accepted to publish in IEEE Transactions on Vehicular Technolog
General Rank Multiuser Downlink Beamforming With Shaping Constraints Using Real-valued OSTBC
In this paper we consider optimal multiuser downlink beamforming in the
presence of a massive number of arbitrary quadratic shaping constraints. We
combine beamforming with full-rate high dimensional real-valued orthogonal
space time block coding (OSTBC) to increase the number of beamforming weight
vectors and associated degrees of freedom in the beamformer design. The
original multi-constraint beamforming problem is converted into a convex
optimization problem using semidefinite relaxation (SDR) which can be solved
efficiently. In contrast to conventional (rank-one) beamforming approaches in
which an optimal beamforming solution can be obtained only when the SDR
solution (after rank reduction) exhibits the rank-one property, in our approach
optimality is guaranteed when a rank of eight is not exceeded. We show that our
approach can incorporate up to 79 additional shaping constraints for which an
optimal beamforming solution is guaranteed as compared to a maximum of two
additional constraints that bound the conventional rank-one downlink
beamforming designs. Simulation results demonstrate the flexibility of our
proposed beamformer design
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