Hieu Duy Nguyen

Multi-Cell Random Beamforming: Achievable Rate and Degrees of Freedom Region

Random beamforming (RBF) is a practically favorable transmission scheme for multiuser multiantenna downlink systems since it requires only partial channel state information (CSI) at the transmitter. Under the conventional single-cell setup, RBF is known to achieve the optimal sum-capacity scaling law as the number of users goes to infinity, thanks to the multiuser diversity enabled transmission scheduling that virtually eliminates the intra-cell interference. In this paper, we extend the study of RBF to a more practical multi-cell downlink system with single-antenna receivers subject to the additional inter-cell interference (ICI). First, we consider the case of finite signal-to-noise ratio (SNR) at each receiver. We derive a closed-form expression of the achievable sum-rate with the multi-cell RBF, based upon which we show an asymptotic sum-rate scaling law as the number of users goes to infinity. Next, we consider the high-SNR regime and for tractable analysis assume that the number of users in each cell scales in a certain order with the per-cell SNR. Under this setup, we characterize the achievable degrees of freedom (DoF) (which is defined as the sum-rate normalized by the logarithm of the SNR as SNR goes to infinity) for the single-cell case with RBF. Then, we extend the analysis to the multi-cell RBF case by characterizing the DoF region, which consists of all the achievable DoF tuples for all the cells subject to their mutual ICI. It is shown that the DoF region characterization provides a useful guideline on how to design a cooperative multi-cell RBF system to achieve optimal throughput tradeoffs among different cells. Furthermore, our results reveal that the multi-cell RBF scheme achieves the “interference-free” DoF region upper bound for the multi-cell system, provided that the per-cell number of users has a sufficiently large scaling order with the SNR. Our result thus confirms the optimality of multi-cell RBF in this regime even without the complete CSI at the transmitter, as compared to other full-CSI requiring transmission schemes such as interference alignment.

Adaptive Compression and Joint Detection for Fronthaul Uplinks in Cloud Radio Access Networks

Cloud radio access network (C-RAN) has recently attracted much attention as a promising architecture for future mobile networks to sustain the exponential growth of data rate. In C-RAN, one data processing center or baseband unit (BBU) communicates with users via distributed remote radio heads (RRHs), which are connected to the BBU via high capacity, low latency fronthaul links. In this paper, we study the compression on fronthaul uplinks and propose a joint decompression algorithm at the BBU. The central premise behind the proposed algorithm is to exploit the correlation between RRHs. Our contribution is threefold. First, we propose a joint decompression and detection (JDD) algorithm which jointly performs decompressing and detecting. The JDD algorithm takes into consideration both the fading and compression effect in a single decoding step. Second, block error rate (BLER) of the proposed algorithm is analyzed in closed-form by using pair-wise error probability analysis. Third, based on the analyzed BLER, we propose adaptive compression schemes subject to quality of service (QoS) constraints to minimize the fronthaul transmission rate while satisfying the pre-defined target QoS. As a dual problem, we also propose a scheme to minimize the signal distortion subject to fronthaul rate constraint. Numerical results demonstrate that the proposed adaptive compression schemes can achieve a compression ratio of 300% in experimental setups.

Multicast Linear Precoding for MIMO-OFDM Systems

Multiple-input multiple-output (MIMO) orthogonal-frequency division multiplexing (OFDM) multicasting system is considered. For a real-time multicast MIMO-OFDM system, we propose a non-iterative and simple linear precoding that consists of a linear sum (LS) of the corresponding channels. Through numerical results, we show that a minimum user rate of the proposed LS precoding is almost identical to its performance upper bound, which can be obtained through max-min rate maximization.

Improper Signaling for Symbol Error Rate Minimization in

The rate maximization for the K-user interference channels (ICs) has been investigated extensively in the literature. However, the practical problem of minimizing the error probability with given signal modulations and/or data rates of the users is less studied. In this paper, by utilizing additional degrees of freedom from the improper signaling (versus the conventional proper signaling) , we seek to optimize the precoding matrices for the K-user single-input single-output (SISO) ICs to minimize pair-wise error probability (PEP) and symbol error rate (SER) with two proposed algorithms, respectively. Compared with conventional proper signaling and other state-of-the-art improper signaling designs, our proposed improper signaling schemes achieve notable error rate improvement in SISO-ICs under both the additive white Gaussian noise (AWGN) and cellular system setups with or without channel coding. Our study provides another viewpoint for optimizing transmissions in ICs and further justifies the practical benefit of improper signaling in interference-limited communication systems.

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This paper derives a new expression of the correlation coefficient for two omni-directional antennas in terms of the easy-to-measure S-parameters. The omni-directional antennas can be monopole or dipole antennas and they are aimed for use in MIMO communication systems whose capacity performance is significantly affected by signal correlation. With this new expression, it can greatly reduce the computational complexity of antenna correlation calculations since the embedded radiation patterns of the antennas are no longer necessary. Numerical calculations demonstrate the accuracy and efficiency of the new formula.

-User Interference Channel

In this paper, we study the downlink performance of two important 5G network architectures, i.e. massive multiple-input multiple-output (M-MIMO) and small-cell densification. We propose a comparative modeling for the two systems, where the user and antenna/base station (BS) locations are distributed according to Poisson point processes (PPPs). We then study the SIR distribution and the outage rate of each network. By comparing these results, we observe that for user-average spectral efficiency, small-cell densification is favorable in crowded areas with moderate to high user density and M-MIMO with low user density. However, small-cell systems outperform M-MIMO in all cases when the performance metric is the energy efficiency. The results of this paper are useful for the optimal design of practical 5G networks.

Correlation coefficient expression by S-parameters for two omni-directional MIMO antennas

In this letter, the gross expenditure, revenue, and profit of a distributed antenna system (DAS) are modeled and investigated. Using stochastic geometry framework, we evaluate the communications pecuniary efficiency (PE) that is defined as a ratio of average achievable bits per expenditure. In addition, we further investigate the ratio of gross revenue over expenditure, which is the PE in economics. From the evaluation of profit and PEs, we justify the economic benefit (profit) of DAS. The PE is expected to be an important decision factor for the deployment of new communication systems, along with typical metrics in communications, namely spectral efficiency and energy efficiency.

Massive MIMO versus small-cell systems: Spectral and energy efficiency comparison

The random beamforming (RBF) scheme, together with multi-user diversity based user scheduling, is able to achieve interference-free downlink transmission with only partial channel state information (CSI) at the transmitter. The impact of receive spatial diversity on RBF, however, is not fully characterized even under a single-cell setup. In this paper, we study a multi-cell multiple-input multiple-output (MIMO) broadcast system with RBF applied at each base station and either the minimum-meansquare-error (MMSE), matched filter (MF), or antenna selection (AS) based spatial receiver applied at each mobile terminal. We investigate the effect of different spatial diversity receivers on the achievable sum-rate of the multi-cell RBF system subject to both the intra- and inter-cell interferences. We focus on the high signal-to-noise ratio (SNR) regime and for a tractable analysis assume that the number of users in each cell scales in a certain order with the per-cell SNR. Under this setup, we characterize the degrees of freedom (DoF) region for the multi-cell RBF system, which constitutes all the achievable sum-rate DoF tuples of all the cells. Our results reveal significant sum-rate DoF gains with the MMSE-based spatial receiver as compared to the case without spatial diversity or with suboptimal spatial receivers (MF or AS). This observation is in sharp contrast to the existing result that spatial diversity only yields marginal sum-rate gains based on the conventional asymptotic analysis in the regime of large number of users but with fixed SNR per cell.

Pecuniary Efficiency of Distributed Antenna Systems

Obtaining accurate instantaneous channel state information (CSI) is challenging for multiple-input-multiple-output (MIMO) systems, particularly if the channel fluctuates rapidly. A more practical assumption is statistical CSI as the channel statistics are likely to remain unchanged for a longer period. In this letter, we propose a precoder design, using only statistical CSI, to minimize error probability for practical MIMO systems with channel estimation errors. Our proposed precoder design is shown to achieve a significant improvement in error performance when compared with other precoding schemes in literature. For example, for a real 4 × 4 MIMO system with BPSK modulation and at a codeword error rate of 10-3, coding gains of up to 12 dB can be achieved.

Effect of receive spatial diversity on the degrees of freedom region in multi-cell random beamforming

A distributed antenna system (DAS) consists of multiple baseband units (BBUs) connecting to distributed antennas (DAs) via dedicated access links. In this study, we investigate a DAS with limited channel state information (CSI) and consider an average rate of users as an objective, where the expectation is taken over the channel uncertainty. We propose two distributed precoder designs that are based on a rate lower bound and a rate upper bound, respectively. As a benchmark, coordinated precoder and cooperative dirty paper coding (DPC)-based precoder with full CSI are compared with our proposed algorithms. Numerical results verifies that the rate performance of our upper-bound based scheme with limited CSI approaches tightly the maximum rates of the full CSI schemes, while that of lower-bound based scheme is relatively worse.