39 research outputs found
Joint Transceiver Design Algorithms for Multiuser MISO Relay Systems with Energy Harvesting
In this paper, we investigate a multiuser relay system with simultaneous
wireless information and power transfer. Assuming that both base station (BS)
and relay station (RS) are equipped with multiple antennas, this work studies
the joint transceiver design problem for the BS beamforming vectors, the RS
amplify-and-forward transformation matrix and the power splitting (PS) ratios
at the single-antenna receivers. Firstly, an iterative algorithm based on
alternating optimization (AO) and with guaranteed convergence is proposed to
successively optimize the transceiver coefficients. Secondly, a novel design
scheme based on switched relaying (SR) is proposed that can significantly
reduce the computational complexity and overhead of the AO based designs while
maintaining a similar performance. In the proposed SR scheme, the RS is
equipped with a codebook of permutation matrices. For each permutation matrix,
a latent transceiver is designed which consists of BS beamforming vectors,
optimally scaled RS permutation matrix and receiver PS ratios. For the given
CSI, the optimal transceiver with the lowest total power consumption is
selected for transmission. We propose a concave-convex procedure based and
subgradient-type iterative algorithms for the non-robust and robust latent
transceiver designs. Simulation results are presented to validate the
effectiveness of all the proposed algorithms
Wireless Information and Energy Transfer for Two-Hop Non-Regenerative MIMO-OFDM Relay Networks
This paper investigates the simultaneous wireless information and energy
transfer for the non-regenerative multipleinput multiple-output orthogonal
frequency-division multiplexing (MIMO-OFDM) relaying system. By considering two
practical receiver architectures, we present two protocols, time switchingbased
relaying (TSR) and power splitting-based relaying (PSR). To explore the system
performance limit, we formulate two optimization problems to maximize the
end-to-end achievable information rate with the full channel state information
(CSI) assumption. Since both problems are non-convex and have no known solution
method, we firstly derive some explicit results by theoretical analysis and
then design effective algorithms for them. Numerical results show that the
performances of both protocols are greatly affected by the relay position.
Specifically, PSR and TSR show very different behaviors to the variation of
relay position. The achievable information rate of PSR monotonically decreases
when the relay moves from the source towards the destination, but for TSR, the
performance is relatively worse when the relay is placed in the middle of the
source and the destination. This is the first time to observe such a
phenomenon. In addition, it is also shown that PSR always outperforms TSR in
such a MIMO-OFDM relaying system. Moreover, the effect of the number of
antennas and the number of subcarriers are also discussed.Comment: 16 pages, 12 figures, to appear in IEEE Selected Areas in
Communication
Transceiver Optimization for Wireless Powered Time-Division Duplex MU-MIMO Systems: Non-Robust and Robust Designs
Wireless powered communication (WPC) has been considered as one of the key technologies in the Internet of Things (IoT) applications. In this paper, we study a wireless powered time-division duplex (TDD) multiuser multiple-input multiple-output (MU-MIMO) system, where the base station (BS) has its own power supply and all users can harvest radio frequency (RF) energy from the BS. We aim to maximize the users' information rates by jointly optimizing the duration of users' time slots and the signal covariance matrices of the BS and users. Different to the commonly used sum rate and max-min rate criteria, the proportional fairness of users' rates is considered in the objective function. We first study the ideal case with the perfect channel state information (CSI), and show that the non-convex proportionally fair rate optimization problem can be transformed into an equivalent convex optimization problem. Then we consider practical systems with imperfect CSI, where the CSI mismatch follows a Gaussian distribution. A chance-constrained robust system design is proposed for this scenario, where the Bernstein inequality is applied to convert the chance constraints into the convex constraints. Finally, we consider a more general case where only partial knowledge of the CSI mismatch is available. In this case, the conditional value-at-risk (CVaR) method is applied to solve the distributionally robust system rate optimization problem. Simulation results are presented to show the effectiveness of the proposed algorithms
Throughput and ergodic capacity of wireless energy harvesting based DF relaying network
In this paper, we consider a decode-and-forward (DF) relaying network based on wireless energy harvesting. The energy constrained relay node first harvests energy through radio-frequency (RF) signals from the source node. Next, the relay node uses the harvested energy to forward the decoded source information to the destination node. The source node transfers energy and information to the relay node through two mechanisms, i) time switching-based relaying (TSR) and ii) power splitting-based relaying (PSR). Considering wireless energy harvesting constraint at the relay node, we derive the exact analytical expressions of the achievable throughput and ergodic capacity of a DF relaying network for both TSR and PSR schemes. Through numerical analysis, we study the throughput performance of the overall system for different system parameters, such as energy harvesting time, power splitting ratio, and signal-to-noise-ratio (SNR). In particular, the throughput performance of the PSR scheme outperforms the throughput performance of the TSR scheme for a wide range of SNRs.ARC Discovery Projects Grant DP14010113