Kaifeng Guo

Uplink power control with MMSE receiver in multi-cell MU-massive-MIMO systems

In the current literature considering multi-cell multi-user massive multiple-input multiple-output (MU-Massive-MIMO) systems, equal uplink power allocation among users is typically assumed, which does not exploit the potential of peruser power control. By contrast, in this paper we apply multi-cell uplink power control, assuming the minimum mean-square-error receiver based on the pilot contaminated channel estimation and a very large but finite number of antennas at the base station. We derive the lower bound on the average post-processing uplink signal to interference-plus-noise ratio (SINR) with individual power assignment between pilot and data transmissions for each user, which facilitates a joint iterative uplink pilot and data power control strategy that minimizes the sum transmit power of all users subject to the per-user SINR and per-user power constraints. The convergence of the proposed algorithm to a unique fixed point optimal solution is discussed for both single- and multi-user scenarios. Numerical results indicate the significance of uplink power control which further improves the energy efficiency in MU-Massive-MIMO systems.

On the performance of EVD-based channel estimations in MU-Massive-MIMO systems

This paper considers the conventional eigenvalue decomposition (EVD) based and widely linear (WL) channel estimations to alleviate inherent pilot contamination problems in multi-cell multi-user massive multiple-input multiple-output (MU-Massive-MIMO) systems. Both channel estimation schemes utilize the asymptotic orthogonality between the propagation vectors of different users which would be true only if the number of base station (BS) antennas goes to infinity. However, the limit on the number of BS antennas plus the error on the sample-based covariance matrix of the received signal deteriorate the channel estimate in practice. We derive therefore the closed-form mean-square-error (MSE) of both channel estimates characterizing two aforementioned error sources, which analytically demonstrates that the WL algorithm is superior to the EVD-based one in two folds: it applies more orthogonalized real representations of channel vectors and reduces a typical phase shift in EVD-based estimate to a sign ambiguity. The performance analysis is verified by our numerical results.

Performance analysis of multi-cell MMSE based receivers in MU-MIMO systems with very large antenna arrays

Uplink minimum mean-square-error (MMSE) detection in multi-user multiple-input multiple-output (MU-MIMO) systems with multi-cell setup is investigated in this paper. We first derive a closed form lower bound on the ergodic achievable uplink rate for each user, assuming perfect channel state information available at the base station.We further analyze and compare the asymptotic performance of an uplink with multi-cell MMSE based detection to its special case of single-cell MMSE detection. The analysis results indicate that the use of large number of base station antennas in multi-cell MU-MIMO systems leads to an increase of energy and spectral efficiency. Our analysis is based on results from random matrix theory and is verified by the simulations.

Security-Constrained Power Allocation in MU-Massive-MIMO With Distributed Antennas

We consider the physical layer security in a multi-user massive multiple-input multiple-output system, where an eavesdropper (Eve) can intercept the information intended for any of the legitimate users. Several remote radio heads (RRHs), each equipped with massive antennas, are deployed to create the distributed antenna system (DAS). With the cooperative maximum-ratio transmission, we propose three secure transmit strategies, i.e., the centralized and autonomous full (CF & AF) transmissions with explicit artificial noise (AN), and the autonomous DAS (AD) scheme using implicit AN. We first derive closed-form deterministic equivalents of the signal to interference-plus-noise ratios (SINRs) of users and Eve for all the schemes. Then, we formulate two security-constrained power allocation problems aiming at: 1) maximizing the minimum user SINR and 2) minimizing the sum transmit power. Except for the optimization in the CF scheme, which yields linear programming, all others result in complementary geometric programming (GP), and are solved by successive approximations into ordinary GP. Numerical results demonstrate: 1) the significance of deploying the RRHs and autonomous power allocation to increase the user SINR; 2) the notable power-saving in the AF scheme; and 3) the improved power reduction in the AD scheme with a limited number of RRHs and antennas per RRH.

Distributed Antennas Aided Secure Communication in MU-Massive-MIMO with QoS Guarantee

We consider in this paper the physical layer security in multi-user massive multiple-input multiple-output (MU-Massive-MIMO) system, where an eavesdropper (Eve) is assumed to be able to intercept the information intended to any of the users. Distributed antenna sets, commonly known as remote radio heads (RRHs), are deployed at the base station, which enables autonomous power allocation between the information signal and artificial noise (AN) at each antenna set. Assuming a large number of antennas at each RRH and cooperative downlink maximum-ratio transmission beamforming, we first derive the closed-form deterministic equivalents of post-processing signal to interference-plus-noise ratio (SINR) of users and Eve in both the centralized and autonomous full transmission schemes. Then, we maximize the minimum user SINR over the signal and AN powers subject to the sum power and Eve SINR constraints. The optimization in the former scheme leads to a linear programming problem, while the latter results in a complementary geometric programming (GP), which has to be transformed into an ordinary GP problem in order to be solved efficiently. Numerical results demonstrate the significance of deploying the RRHs as well as autonomous power allocation to improve the user SINR along with the secure communication with QoS guarantee in MU-Massive-MIMO.

An Overview of Massive MIMO Technology Components in METIS

As the standardization of full-dimension MIMO systems in the Third Generation Partnership Project progresses, the research community has started to explore the potential of very large arrays as an enabler technology for meeting the requirements of fifth generation systems. Indeed, in its final deliverable, the European 5G project METIS identifies massive MIMO as a key 5G enabler and proposes specific technology components that will allow the cost-efficient deployment of cellular systems taking advantage of hundreds of antennas at cellular base stations. These technology components include handling the inherent pilot-data resource allocation trade-off in a near optimal fashion, a novel random access scheme supporting a large number of users, coded channel state information for sparse channels in frequency- division duplexing systems, managing user grouping and multi-user beamforming, and a decentralized coordinated transceiver design. The aggregate effect of these components enables massive MIMO to contribute to the METIS objectives of delivering very high data rates and managing dense populations.

Performance analysis of downlink MMSE beamforming training in TDD MU-massive-MIMO

We consider a time-division duplexing multi-user massive multiple-input multiple-output system, where a so-called beamforming training (BFT) occurs prior to the downlink (DL) data transmission. The BFT process helps the users to obtain the estimates of effective channels, and thus facilitates a more reliable DL data detection compared to the conventional case, where the users have only the statistic channel knowledge. We first derive the closed-form lower bounds on the achievable DL data rates in the conventional and BFT schemes, using the minimum mean-square-error (MMSE) precoder. This enables us to further analyze the spectral efficiency, which takes the loss due to the training overhead into account. Moreover, we also consider a realistic scenario where the channel aging is present: it may destroy the training gain and lead to an efficiency loss. The effects of channel aging in both schemes are evaluated. In simulations, the performance of MMSE precoder is compared to the maximum-ratio transmission and zero-forcing precoding methods for both schemes in the static and aging channels.

Massive MIMO Aided Secure Multi-Pair Relaying with Power Control

We consider in this paper the physical layer security of multi-pair communication in massive MIMO aided amplify-and-forward (AF) relaying, where an eavesdropper (Eve) may intercept the information intended to any of the destinations. We derive closed-form deterministic equivalents of the end-to-end signal to interference-plus-noise ratios of legitimate users and Eve. We assume that the AF processing as well as the artificial noise generated at the relay are based on the imperfect channel state information of both hops. A particular result of the asymptotic analysis shows that by simply increasing the transmit power at the sources or relay the reachable security is limited by an upper bound. Nevertheless, the security can be strongly improved with a low-complexity power control at the relay, whose performance is evaluated in simulations.

Massive MIMO relaying assisted D2D with opportunistic energy harvesting

In this paper, massive MIMO amplify-and-forward multi-pair relaying is considered to assist device-to-device (D2D) communications. The direct D2D communication is underlaid with the source-to-relay transmission in the first hop, hence the D2D signals are also received at the relay, which are then forwarded in the second hop, overlapping with the relay-to-destination transmission. Moreover, D2D users are assumed to be able to harvest energy from the relay signal. Therefore, the D2D receivers, who failed in the direct D2D, can perform information detection (ID) with an opportunistic energy harvesting (EH) in the second hop. Closed-form deterministic equivalents of the associated signal to interference-plus-noise ratio in the ID and the harvested energy in the EH are derived, for both the maximum ratio combining/transmission and zero-forcing based relaying. A particular result of the asymptotic analysis indicates that the transmit power of source users can be made inversely proportional to the number of relay antennas, such that non-vanishing relay assisted D2D rate and harvested energy of D2D users exist. Simulations validate the analytical results, and illustrate the capability of massive MIMO relaying in assisting D2D via the so-called rate-energy region.

Power-Saving Transmission in MU-Massive-MIMO with Distributed Antennas and Security Guarantee

The physical layer security in a multi-user massive multiple-input multiple-output (MU-Massive-MIMO) system is considered in this paper, where a hidden eavesdropper (Eve) may eavesdrop the information signal of any legitimate user. Two distributed antenna system (DAS) aided power-saving transmit strategies are evaluated: 1) the autonomous full (AF) transmission with explicit artificial noise (AN), and 2) the autonomous DAS (AD) scheme, in which the AN is implicitly generated. Based on the cooperative maximum-ratio transmission and derived closed-form deterministic equivalents of the signal to interference-plus-noise ratios (SINRs) of users and Eve, we minimize the sum transmit power subject to the security constraints on the SINRs. The optimizations in both schemes are complementary geometric programming. In particular, the AD scheme depends on the signal to AN power ratio, which is controlled either by an unified or autonomous multiplicative parameter. In simulations, we illustrate that the sum power consumed in the AD scheme with autonomous parameter is less than the unified case as well as the AF scheme, hence it improves the power-saving in MU-Massive-MIMO with security guarantee.