Secure Massive MIMO Communication with Low-resolution DACs

In this paper, we investigate secure transmission in a massive multiple-input multiple-output (MIMO) system adopting low-resolution digital-to-analog converters (DACs). Artificial noise (AN) is deliberately transmitted simultaneously with the confidential signals to degrade the eavesdropper's channel quality. By applying the Bussgang theorem, a DAC quantization model is developed which facilitates the analysis of the asymptotic achievable secrecy rate. Interestingly, for a fixed power allocation factor $\phi$, low-resolution DACs typically result in a secrecy rate loss, but in certain cases they provide superior performance, e.g., at low signal-to-noise ratio (SNR). Specifically, we derive a closed-form SNR threshold which determines whether low-resolution or high-resolution DACs are preferable for improving the secrecy rate. Furthermore, a closed-form expression for the optimal $\phi$ is derived. With AN generated in the null-space of the user channel and the optimal $\phi$, low-resolution DACs inevitably cause secrecy rate loss. On the other hand, for random AN with the optimal $\phi$, the secrecy rate is hardly affected by the DAC resolution because the negative impact of the quantization noise can be compensated for by reducing the AN power. All the derived analytical results are verified by numerical simulations.Comment: 14 pages, 10 figure

Transmitting Data Through Reconfigurable Intelligent Surface: A Spatial Sigma-Delta Modulation Approach

Transmitting data using the phases on reconfigurable intelligent surfaces (RIS) is a promising solution for future energy-efficient communication systems. Recent work showed that a virtual phased massive multiuser multiple-input-multiple-out (MIMO) transmitter can be formed using only one active antenna and a large passive RIS. In this paper, we are interested in using such a system to perform MIMO downlink precoding. In this context, we may not be able to apply conventional MIMO precoding schemes, such as the simple zero-forcing (ZF) scheme, and we typically need to design the phase signals by solving optimization problems with constant modulus constraints or with discrete phase constraints, which pose challenges with high computational complexities. In this work, we propose an alternative approach based on Sigma-Delta ($\Sigma\Delta$) modulation, which is classically famous for its noise-shaping ability. Specifically, first-order $\Sigma\Delta$ modulation is applied in the spatial domain to handle phase quantization in generating constant envelope signals. Under some mild assumptions, the proposed phased $\Sigma\Delta$ modulator allows us to use the ZF scheme to synthesize the RIS reflection phases with negligible complexity. The proposed approach is empirically shown to achieve comparable bit error rate performance to the unquantized ZF scheme

Performance Analysis of Indoor THz Communications with One-Bit Precoding

In this paper, the performance of indoor Terahertz (THz) communication systems with one-bit digital-to- analog converters (DACs) is investigated. Array-of- subarrays architecture is assumed for the antennas at the access points, where each RF chain uniquely activates a disjoint subset of antennas, each of which is connected to an exclusive phase shifter. Hybrid precoding, including maximum ratio transmission (MRT) and zero-forcing (ZF) precoding, is considered. The best beamsteering direction for the phase shifter in the large subarray antenna regime is first proved to be the direction of the line-of-sight (LoS) path. Subsequently, the closed-form expression of the lower- bound of the achievable rate in the large subarray antenna regime is derived, which is the same for both MRT and ZF and is independent of the transmit power. Numerical results validating the analysis are provided as well

Low complexity precoding schemes for massive MIMO systems

PhD ThesisIn order to deal with the challenges of the exponentially growing communication traffic and spectrum bands with wider bandwidth, massive MIMO technology was been proposed, which employs an unprecedented number of base station antennas simultaneously to serve a smaller number of user terminals in the same channel. Although the very large antenna arrays for massive multiple-input multiple-output (MIMO) systems lead to unprecedented data throughputs and beamforming gains to meet these data traffic demands, they also lead to prohibitively high energy consumption and hardware complexity. In terms of precoding schemes, the conventional linear precoding entirely processes the complex signals in the digital domain and then upconverts to the carrier frequency after passing through radio frequency (RF) chains, which can achieve near-optimal performance with the large antenna arrays. However, it is infeasible because with fully digital precoding, every antenna element needs to be coupled with one RF chain, including the digital-toanalog convertors, mixers and filters, which is accountable for excessively high hardware cost and power consumption. This thesis focuses on the design and analysis of low complexity precoding schemes. The novel contributions in this thesis are presented in three sections. First, a low complexity hybrid precoding scheme is proposed for the downlink transmission of massive multi-user MIMO systems with a finite dimensional channel model. By analysing the structure of the channel model, the beamsteering codebooks are combined with extracting the phase of the conjugate transpose of the fast fading matrix to design the RF precoder, which thereby harvests the large array gain achieved by an unprecedented number of base station antennas. Then a baseband precoder is designed based on the equivalent channel with zero forcing (ZF) precoding. In addition, a tight upper bound on the spectral efficiency is derived and the performance of hybrid precoding is investigated. Second, based on successive refinement, a new iterative hybrid precoding scheme is proposed with a sub-connected architecture for mmWave MIMO systems.In each iteration, the first step is to design the RF precoder and the second step is to design the baseband precoder. The RF precoder is regarded as an input to update the baseband precoder until the stopping criterion is triggered. Phase extraction is used to obtain the RF precoder and then the baseband precoder is optimized by the orthogonal property. This algorithm effectively optimizes the hybrid precoders and reduces the hardware complexity with sub-connected architecture. A closed-form expression of upper bound for the spectral efficiency is derived and the energy efficiency and the complexity of the proposed hybrid precoding scheme are analyzed. Finally, the use of low-resolution digital-to-analog converters (DACs) for each antenna and RF chain is considered. Moreover, in a more practical scenario, the hardware mismatch between the uplink and the downlink for the channel matrix is a focus, where the downlink is not the transpose of the uplink in time-division duplex mode. The impact of one-bit DACs on linear precoding is studied for the massive MIMO systems with hardware mismatch. Using the Bussgang theorem and random matrix theorem, a closed-form expression for the signal to quantization, interference and noise ratio with consideration of hardware mismatch and one-bit ZF precoding is derived, which can be used to derive the achiev- able rate. Then a performance approximation is also derived in the high signal-to-noise ratio (SNR) region, which is related to the ratio of the number of base station antennas and the number of mobile users , and the statistics of the circuit gains at the base station. In conclusion, analytical and numerical results show that the proposed techniques are able to achieve close-to-optimal performances with low hardware complexity, thus the low complexity precoding schemes can be valid candidates for practical implementations of modern communication systems