802 research outputs found
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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MMSE-based beamforming techniques for relay broadcast channels
We propose minimum mean square error (MMSE) based beamforming techniques for a multiantenna relay network, where a base station (BS) equipped with multiple antennas communicates with a number of single antenna users through a multiantenna relay.We specifically solve three optimization problems: a) sum-power minimization problem b) mean square error (MSE) balancing problem and c)mixed quality of services (QoS) problem. Unfortunately, these problems are not jointly convex in terms of beamforming vectors at the BS and the relay amplification matrix. To circumvent this non-convexity issue, the original problems are divided into two subproblems where the beamforming vectors and the relay amplification matrix are alternately optimized while other one is fixed. Three iterative algorithms have been developed based on convex optimization techniques and general MSE duality. Simulation results have been provided to validate the convergence of the proposed algorithms
Mathematical optimization and game theoretic techniques for multicell beamforming
The main challenge in mobile wireless communications is the incompatibility between limited wireless resources and increasing demand on wireless services. The employment of frequency reuse technique has effectively increased the capacity of the network and improved the efficiency of frequency utilization. However, with the emergence of smart phones and even more data hungry applications such as interactive multimedia, higher data rate is demanded by mobile users. On the other hand, the interference induced by
spectrum sharing arrangement has severely degraded the quality of service for users and restricted further reduction of cell size and enhancement of frequency reuse factor.
Beamforming technique has great potential to improve the network performance. With the employment of multiple antennas, a base station is capable of directionally transmitting signals to desired users through narrow beams rather than omnidirectional waves. This will result users suffer less interference from the signals transmitted to other co-channel users. In addition, with the combination of beamforming technique and appropriate power control schemes, the resources of the wireless networks can be used more efficiently.
In this thesis, mathematical optimization and game theoretic techniques have been exploited for beamforming designs within the context of multicell
wireless networks. Both the coordinated beamforming and the coalitional game theoretic based beamforming techniques have been proposed. Initially, coordinated multicell beamforming algorithms for mixed design criteria have been developed, in which some users are allowed to achieve target signal-to-interference-
plus-noise ratios (SINRs) while the SINRs of rest of the users in all cells will be balanced to a maximum achievable SINR. An SINR balancing based coordinated multicell beamforming algorithm has then been proposed which is capable of balancing users in different cells to different SINR levels. Finally, a coalitional game based multicell beamforming has been considered, in which the proposed coalition formation algorithm can reach to stable coalition structures. The performances of all the proposed algorithms have been demonstrated using MATLAB based simulations
MMSE-based beamforming techniques for relay broadcast channels
We propose minimum mean square error (MMSE)-based beamforming techniques for a multiantenna relay network, where a base station (BS) equipped with multiple antennas communicates with a number of single-antenna users through a multiantenna relay. We specifically solve three optimization problems, namely, 1) the sum-power minimization problem, 2) the mean-square-error (MSE) balancing problem, and 3) the mixed quality-of-service (QoS) problem. Unfortunately, these problems are not jointly convex in terms of beamforming vectors at the BS and the relay amplification matrix. To circumvent this nonconvexity issue, the original problems are divided into two subproblems, where the beamforming vectors and the relay amplification matrix are alternately optimized, whereas the other is fixed. Three iterative algorithms are developed based on convex optimization techniques and general MSE duality. Simulation results are provided to validate the convergence of the proposed algorithms
Massive MIMO Multicasting in Noncooperative Cellular Networks
We study the massive multiple-input multiple-output (MIMO) multicast
transmission in cellular networks where each base station (BS) is equipped with
a large-scale antenna array and transmits a common message using a single
beamformer to multiple mobile users. We first show that when each BS knows the
perfect channel state information (CSI) of its own served users, the
asymptotically optimal beamformer at each BS is a linear combination of the
channel vectors of its multicast users. Moreover, the optimal combining
coefficients are obtained in closed form. Then we consider the imperfect CSI
scenario where the CSI is obtained through uplink channel estimation in
timedivision duplex systems. We propose a new pilot scheme that estimates the
composite channel which is a linear combination of the individual channels of
multicast users in each cell. This scheme is able to completely eliminate pilot
contamination. The pilot power control for optimizing the multicast beamformer
at each BS is also derived. Numerical results show that the asymptotic
performance of the proposed scheme is close to the ideal case with perfect CSI.
Simulation also verifies the effectiveness of the proposed scheme with finite
number of antennas at each BS.Comment: to appear in IEEE JSAC Special Issue on 5G Wireless Communication
System
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
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