5,671 research outputs found

    Bit Allocation Law for Multi-Antenna Channel Feedback Quantization: Single-User Case

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    This paper studies the design and optimization of a limited feedback single-user system with multiple-antenna transmitter and single-antenna receiver. The design problem is cast in form of the minimizing the average transmission power at the base station subject to the user's outage probability constraint. The optimization is over the user's channel quantization codebook and the transmission power control function at the base station. Our approach is based on fixing the outage scenarios in advance and transforming the design problem into a robust system design problem. We start by showing that uniformly quantizing the channel magnitude in dB scale is asymptotically optimal, regardless of the magnitude distribution function. We derive the optimal uniform (in dB) channel magnitude codebook and combine it with a spatially uniform channel direction codebook to arrive at a product channel quantization codebook. We then optimize such a product structure in the asymptotic regime of Bβ†’βˆžB\rightarrow \infty, where BB is the total number of quantization feedback bits. The paper shows that for channels in the real space, the asymptotically optimal number of direction quantization bits should be (Mβˆ’1)/2{(M{-}1)}/{2} times the number of magnitude quantization bits, where MM is the number of base station antennas. We also show that the performance of the designed system approaches the performance of the perfect channel state information system as 2βˆ’2BM+12^{-\frac{2B}{M+1}}. For complex channels, the number of magnitude and direction quantization bits are related by a factor of (Mβˆ’1)(M{-}1) and the system performance scales as 2βˆ’BM2^{-\frac{B}{M}} as Bβ†’βˆžB\rightarrow\infty.Comment: Submitted to IEEE Transactions on Signal Processing, March 201

    Grassmannian Beamforming for MIMO Amplify-and-Forward Relaying

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    In this paper, we derive the optimal transmitter/ receiver beamforming vectors and relay weighting matrix for the multiple-input multiple-output amplify-and-forward relay channel. The analysis is accomplished in two steps. In the first step, the direct link between the transmitter (Tx) and receiver (Rx) is ignored and we show that the transmitter and the relay should map their signals to the strongest right singular vectors of the Tx-relay and relay-Rx channels. Based on the distributions of these vectors for independent identically distributed (i.i.d.) Rayleigh channels, the Grassmannian codebooks are used for quantizing and sending back the channel information to the transmitter and the relay. The simulation results show that even a few number of bits can considerably increase the link reliability in terms of bit error rate. For the second step, the direct link is considered in the problem model and we derive the optimization problem that identifies the optimal Tx beamforming vector. For the i.i.d Rayleigh channels, we show that the solution to this problem is uniformly distributed on the unit sphere and we justify the appropriateness of the Grassmannian codebook (for determining the optimal beamforming vector), both analytically and by simulation. Finally, a modified quantizing scheme is presented which introduces a negligible degradation in the system performance but significantly reduces the required number of feedback bits.Comment: Submitted to IEEE Journal of Selected Areas in Communications, Special Issue on Exploiting Limited Feedback in Tomorrows Wireless Communication Network
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