1,745 research outputs found
Joint Wireless Information and Energy Transfer with Reduced Feedback in MIMO Interference Channels
To determine the transmission strategy for joint wireless information and
energy transfer (JWIET) in the MIMO interference channel (IFC), the information
access point (IAP) and energy access point (EAP) require the channel state
information (CSI) of their associated links to both the information-decoding
(ID) mobile stations (MSs) and energy-harvesting (EH) MSs (so-called local
CSI). In this paper, to reduce th e feedback overhead of MSs for the JWIET in
two-user MIMO IFC, we propose a Geodesic energy beamforming scheme that
requires partial CSI at the EAP. Furthermore, in the two-user MIMO IFC, it is
proved that the Geodesic energy beamforming is the optimal strategy. By adding
a rank-one constraint on the transmit signal covariance of IAP, we can further
reduce the feedback overhead to IAP by exploiting Geodesic information
beamforming. Under the rank-one constraint of IAP's transmit signal, we prove
that Geodesic information/energy beamforming approach is the optimal strategy
for JWIET in the two-user MIMO IFC. We also discuss the extension of the
proposed rank-one Geodesic information/energy beamforming strategies to general
K-user MIMO IFC. Finally, by analyzing the achievable rate-energy performance
statistically under imperfect partial CSIT, we propose an adaptive bit
allocation strategy for both EH MS and ID MS.Comment: accepted to IEEE Journal of Selected Areas in Communications (IEEE
JSAC), Special Issue on Wireless Communications Powered by Energy Harvesting
and Wireless Energy Transfe
Multiuser Millimeter Wave Beamforming Strategies with Quantized and Statistical CSIT
To alleviate the high cost of hardware in mmWave systems, hybrid
analog/digital precoding is typically employed. In the conventional two-stage
feedback scheme, the analog beamformer is determined by beam search and
feedback to maximize the desired signal power of each user. The digital
precoder is designed based on quantization and feedback of effective channel to
mitigate multiuser interference. Alternatively, we propose a one-stage feedback
scheme which effectively reduces the complexity of the signalling and feedback
procedure. Specifically, the second-order channel statistics are leveraged to
design digital precoder for interference mitigation while all feedback overhead
is reserved for precise analog beamforming. Under a fixed total feedback
constraint, we investigate the conditions under which the one-stage feedback
scheme outperforms the conventional two-stage counterpart. Moreover, a rate
splitting (RS) transmission strategy is introduced to further tackle the
multiuser interference and enhance the rate performance. Consider (1) RS
precoded by the one-stage feedback scheme and (2) conventional transmission
strategy precoded by the two-stage scheme with the same first-stage feedback as
(1) and also certain amount of extra second-stage feedback. We show that (1)
can achieve a sum rate comparable to that of (2). Hence, RS enables remarkable
saving in the second-stage training and feedback overhead.Comment: submitted to TW
Joint Iterative Optimization Based Low-Complexity Adaptive Hybrid Beamforming for Massive MU-MIMO Systems
IEEE This paper proposes a joint iterative optimization based hybrid beamforming technique for massive MU-MIMO systems. The proposed technique jointly and iteratively optimizes the transmitter precoders and combiners, aiming to approach the global optimum solution for the system sum-rate maximization problem. The proposed technique develops an adaptive algorithm exploiting the stochastic gradients (SG) of the local beamformers and provides low-complexity closed-form solutions. Furthermore, an efficient adaptive scheme is developed based on the proposed adaptive algorithm and the closed-form solutions. The proposed algorithm requires the signal-to-interference-plus-noise ratio (SINR) feedback from each user and a limited size transition vector to be exchanged between the transmitter and receivers at each step to update beamformers locally. Analytic result shows that the proposed adaptive algorithm achieves low-complexity when the array size is large and is able to converge within a small number of iterations. Simulation result shows that the proposed technique is able to achieve superior performance comparing to the existing state-of-art techniques. In addition, the knowledge of instantaneous channel state information (CSI) is not required as the channels are also adaptively estimated with each coherence time which is a practical assumption since the CSI is usually unavailable or have time-varying nature in real-time applications
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