Transmit Power Minimization for MIMO Systems of Exponential Average BER with Fixed Outage Probability

This document is the Accepted Manuscript version of the following article: Dian-Wu Yue, and Yichuang Sun, ‘Transmit Power Minimization for MIMO Systems of Exponential Average BER with Fixed Outage Probability’, Wireless Personal Communications, Vol. 90 (4): 1951-1970, first available online on 20 June 2016. Under embargo. Embargo end date: 20 June 2017. The final publication is available at Springer via https://link.springer.com/article/10.1007%2Fs11277-016-3432-4This paper is concerned with a wireless multiple-antenna system operating in multiple-input multiple-output (MIMO) fading channels with channel state information being known at both transmitter and receiver. By spatiotemporal subchannel selection and power control, it aims to minimize the average transmit power (ATP) of the MIMO system while achieving an exponential type of average bit error rate (BER) for each data stream. Under the constraints on each subchannel that individual outage probability and average BER are given, based on a traditional upper bound and a dynamic upper bound of Q function, two closed-form ATP expressions are derived, respectively, which can result in two different power allocation schemes. Numerical results are provided to validate the theoretical analysis, and show that the power allocation scheme with the dynamic upper bound can achieve more power savings than the one with the traditional upper bound.Peer reviewe

Distortion Minimization in Gaussian Layered Broadcast Coding with Successive Refinement

A transmitter without channel state information (CSI) wishes to send a delay-limited Gaussian source over a slowly fading channel. The source is coded in superimposed layers, with each layer successively refining the description in the previous one. The receiver decodes the layers that are supported by the channel realization and reconstructs the source up to a distortion. The expected distortion is minimized by optimally allocating the transmit power among the source layers. For two source layers, the allocation is optimal when power is first assigned to the higher layer up to a power ceiling that depends only on the channel fading distribution; all remaining power, if any, is allocated to the lower layer. For convex distortion cost functions with convex constraints, the minimization is formulated as a convex optimization problem. In the limit of a continuum of infinite layers, the minimum expected distortion is given by the solution to a set of linear differential equations in terms of the density of the fading distribution. As the bandwidth ratio b (channel uses per source symbol) tends to zero, the power distribution that minimizes expected distortion converges to the one that maximizes expected capacity. While expected distortion can be improved by acquiring CSI at the transmitter (CSIT) or by increasing diversity from the realization of independent fading paths, at high SNR the performance benefit from diversity exceeds that from CSIT, especially when b is large.Comment: Accepted for publication in IEEE Transactions on Information Theor

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

On the Design of Artificial-Noise-Aided Secure Multi-Antenna Transmission in Slow Fading Channels

In this paper, we investigate the design of artificial-noise-aided secure multi-antenna transmission in slow fading channels. The primary design concerns include the transmit power allocation and the rate parameters of the wiretap code. We consider two scenarios with different complexity levels: i) the design parameters are chosen to be fixed for all transmissions, ii) they are adaptively adjusted based on the instantaneous channel feedback from the intended receiver. In both scenarios, we provide explicit design solutions for achieving the maximal throughput subject to a secrecy constraint, given by a maximum allowable secrecy outage probability. We then derive accurate approximations for the maximal throughput in both scenarios in the high signal-to-noise ratio region, and give new insights into the additional power cost for achieving a higher security level, whilst maintaining a specified target throughput. In the end, the throughput gain of adaptive transmission over non-adaptive transmission is also quantified and analyzed.Comment: to appear in IEEE Transactions on Vehicular Technolog

Multicast Multigroup Precoding and User Scheduling for Frame-Based Satellite Communications

The present work focuses on the forward link of a broadband multibeam satellite system that aggressively reuses the user link frequency resources. Two fundamental practical challenges, namely the need to frame multiple users per transmission and the per-antenna transmit power limitations, are addressed. To this end, the so-called frame-based precoding problem is optimally solved using the principles of physical layer multicasting to multiple co-channel groups under per-antenna constraints. In this context, a novel optimization problem that aims at maximizing the system sum rate under individual power constraints is proposed. Added to that, the formulation is further extended to include availability constraints. As a result, the high gains of the sum rate optimal design are traded off to satisfy the stringent availability requirements of satellite systems. Moreover, the throughput maximization with a granular spectral efficiency versus SINR function, is formulated and solved. Finally, a multicast-aware user scheduling policy, based on the channel state information, is developed. Thus, substantial multiuser diversity gains are gleaned. Numerical results over a realistic simulation environment exhibit as much as 30% gains over conventional systems, even for 7 users per frame, without modifying the framing structure of legacy communication standards.Comment: Accepted for publication to the IEEE Transactions on Wireless Communications, 201

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

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 $B\rightarrow \infty$, where $B$ 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 ${(M{-}1)}/{2}$ times the number of magnitude quantization bits, where $M$ 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 $2^{-\frac{2B}{M+1}}$. For complex channels, the number of magnitude and direction quantization bits are related by a factor of $(M{-}1)$ and the system performance scales as $2^{-\frac{B}{M}}$ as $B\rightarrow\infty$.Comment: Submitted to IEEE Transactions on Signal Processing, March 201