Hongbo Zhu

Power Scaling of Uplink Massive MIMO Systems With Arbitrary-Rank Channel Means

This paper investigates the uplink achievable rates of massive multiple-input multiple-output (MIMO) antenna systems in Ricean fading channels, using maximal-ratio combining (MRC) and zero-forcing (ZF) receivers, assuming perfect and imperfect channel state information (CSI). In contrast to previous relevant works, the fast fading MIMO channel matrix is assumed to have an arbitrary-rank deterministic component as well as a Rayleigh-distributed random component. We derive tractable expressions for the achievable uplink rate in the large-antenna limit, along with approximating results that hold for any finite number of antennas. Based on these analytical results, we obtain the scaling law that the users transmit power should satisfy, while maintaining a desirable quality of service. In particular, it is found that regardless of the Ricean K-factor, in the case of perfect CSI, the approximations converge to the same constant value as the exact results, as the number of base station antennas, M, grows large, while the transmit power of each user can be scaled down proportionally to 1/M. If CSI is estimated with uncertainty, the same result holds true but only when the Ricean K-factor is non-zero. Otherwise, if the channel experiences Rayleigh fading, we can only cut the transmit power of each user proportionally to 1/√M. In addition, we show that with an increasing Ricean K-factor, the uplink rates will converge to fixed values for both MRC and ZF receivers.

Large System Secrecy Rate Analysis for SWIPT MIMO Wiretap Channels

In this paper, we study the multiple-input multiple-output wiretap channel for simultaneous wireless information and power transfer, in which there is a base station (BS), an information-decoding (ID) user, and an energy-harvesting (EH) user. The messages intended to the ID user is required to be kept confidential to the EH user. Our objective is to design the optimal transmit covariance matrix at the BS for maximizing the ergodic secrecy rate subject to the harvested energy requirement for the EH user exploiting only statistical channel state information at the BS. To this end, we begin by deriving an approximation for the ergodic secrecy rate using large-dimensional random matrix theory and the method of Taylor series expansion. This approximation enables us to derive the asymptotic-optimal transmit covariance matrix that achieves the tradeoff for ergodic secrecy rate and harvested energy. The simulation results are provided to verify the accuracy of the approximation and show that a bigger rate-energy region can be achieved when the Rician factor increases or the path loss exponent decreases. We also show that when the transmit correlation increases or the distance between the eavesdropper and the BS decreases, the harvested energy will be increased, while the achieved ergodic secrecy rate decreases.

Joint wireless information and energy transfer in massive distributed antenna systems

In mobile communications, two potentially ground-breaking ideas have emerged in recent years: massive MIMO antenna technology, which delivers enormous information rates, and wireless energy transfer (WET), which makes remote charging of mobile users possible. This article realizes the huge potential of combining the two for high wireless information transfer (WIT) and WET. In particular, to maximize the synergy, the distributed version of massive MIMO (known as massive distributed antenna system, MDAS) is advocated to go with the joint wireless information and energy transfer (JWIET) system capable of both WIT and WET. We present the opportunities in MDAS-JWIET, and discuss research trends in MDAS with several architectures involving WET and WIT.

Outage probability of device-to-device communication assisted by one-way amplify-and-forward relaying

This study investigates the outage probability of device-to-device communication assisted by a relay node utilising a one-way amplify-and-forward relaying strategy. The authors assume that all the terminals are equipped with a single antenna and all the users know perfect channel state information. They first derive the exact closed-form expression for characterising the outage probability performance of the system. They subsequently discuss several special scenarios and obtain the asymptotic results for each of the considered scenarios. The results can be easily computed with only the channel statistics. Based on the analysis in the high signal-to-noise ratio regime, closed-form power allocation policies are developed to improve the outage probability performance. The authors analytical results are validated via Monte Carlo computer simulations.

Beamforming and Interference Cancellation for D2D Communication Underlaying Cellular Networks

This paper presents an analytical performance investigation of both beamforming (BF) and interference cancellation (IC) strategies for a device-to-device (D2D) communication system underlaying a cellular network with an M-antenna base station (BS). We first derive new closed-form expressions for the ergodic achievable rate for BF and IC precoding strategies with quantized channel state information (CSI), as well as, perfect CSI. Then, novel lower and upper bounds are derived which apply for an arbitrary number of antennas and are shown to be sufficiently tight to the Monte-Carlo results. Based on these results, we examine in detail three important special cases including: high signal-to-noise ratio (SNR), weak interference between cellular link and D2D link, and BS equipped with a large number of antennas. We also derive asymptotic expressions for the ergodic achievable rate for these scenarios. Based on these results, we obtain valuable insights into the impact of the system parameters, such as the number of antennas, SNR and the interference for each link. In particular, we show that an irreducible saturation point exists in the high SNR regime, while the ergodic rate under IC strategy is verified to be always better than that under BF strategy. We also reveal that the ergodic achievable rate under perfect CSI scales as log2M, whilst it reaches a ceiling with quantized CSI.

Uplink rate analysis of multicell massive MIMO systems in Ricean fading

In this paper, we investigate the uplink rate of multicell massive multiple-input multiple-output (MIMO) systems. We assume the channel is estimated through uplink training with MMSE estimation. Unlike previous studies, the channel between users and the base station (BS) in the same cell is modeled to be Ricean fading, in which the fast fading matrix is assumed to have a deterministic component as well as a Rayleigh-distributed random component, and the Ricean K-factor of each user is supposed to be different. The effect of pilot contamination is analyzed and we derive a closed-form approximation for the achievable uplink rate that holds for any finite number of BS antennas (M). Based on it, we find that increasing the proportion of line-of-sight (LOS) component can improve the uplink performance. In particular, with both very large M and Ricean K-factor, the uplink rate grows infinite, which means that the pilot contamination can be eliminated completely. However, the increase of users transmit power will make the uplink rate approach a constant value even with unlimited M. In addition, we show that with no reduction in the rate performance, each users power can be most scaled down to 1/√M with Rayleigh fading channel and to 1/M with non-zero Ricean K-factor.

Achievable ergodic secrecy rate for MIMO SWIPT wiretap channels

In this paper, we study the multiple-input multiple-output (MIMO) wiretap channel performing simultaneous wireless information and power transfer (SWIPT), where there are a multiple-antenna base station (BS), a multiple-antenna information decoding (ID) user, and a multiple-antenna energy harvesting (EH) user. The messages intended to the ID user need to be kept confidential to the EH user. The channels between BS and users are modeled as fading channels with different spatial correlations and line-of-sight (LoS) components. We assume that only statistical channel state information (CSI) is available at the BS. Our objective is to design the optimal transmit covariance matrix at the BS for maximizing the ergodic secrecy rate subject to the BS power constraint and the harvested energy requirement for the EH user. To this end, we present an approximation for the ergodic secrecy rate by using large dimensional random matrix theory and the method of Taylor series expansion. Based on this, an iterative algorithm is proposed to find the transmit covariance matrix. Simulation results are provided to verify the accuracy of the approximation and the performance of the design.

Outage analysis for device-to-device communication assisted by two-way decode-and-forward relaying

In this paper, we investigate the outage probability of device-to-device (D2D) communication assisted by decode-and-forward (DF) relay node and that using traditional strategy. We assume all terminals are equipped with single-antenna. We first derive closed-form expressions for the outage probability of the D2D link under asymmetrical and symmetrical cases respectively. Then we derive tight approximations of the outage behavior in the high signal-to-noise (SNR) regime under the two cases. Based on these results, we then show that the D2D communication aided by DF relay node gains advantages over that of the traditional strategy without extra power. Numerical results demonstrate that the analytical results are accurate on various conditions.

Wireless Information and Power Transfer Design for Energy Cooperation Distributed Antenna Systems

Distributed antenna systems (DASs) have been widely implemented in the state-of-the-art cellular communication systems to cover dead spots. Recent studies have also indicated that DAS has advantages in wireless energy transfer (WET). In this paper, we study simultaneous wireless information and power transfer for a multiple-input single-output DAS in the downlink, which consists of arbitrarily distributed remote antenna units (RAUs). In order to save the energy cost, we adopt the energy cooperation of energy harvesting (EH) and two-way energy flows to let the RAUs trade their harvested energy through the smart grid network. Under individual EH constraints, per-RAU power constraints, and various smart grid considerations, we investigate a power management strategy that determines how to utilize the stochastically spatially distributed harvested energy at the RAUs and how to trade the energy with the smart grid simultaneously to supply maximum wireless information transfer (WIT) with a minimum WET constraint for a receiver adopting power splitting. Our analysis shows that the optimal design can be achieved in two steps. The first step is to maximize a new objective that can simultaneously maximize both WET and WIT, considering both the smart grid profitable and smart grid neutral cases. For the grid-profitable case, we derive the optimal full power strategy and provide a closed-form result to see under what condition this strategy is used. On the other hand, for the grid-neutral case, we illustrate that the optimal power policy has a double-threshold structure and present an optimal allocation strategy. The second step is then to solve the whole problem by obtaining the splitting power ratio based on the minimum WET constraint. Simulation results are provided to evaluate the performance under various settings and characterize the double-threshold structure.

Power scaling of massive MIMO systems with arbitrary-rank channel means and imperfect CSI

In this paper, we study the achievable uplink rates of massive multiple-input multiple-output (MIMO) systems using maximal-ratio combining (MRC) and zero-forcing (ZF) receivers, assuming imperfect channel state information (CSI). Unlike all previous studies, the fast fading MIMO channel matrix here is modeled to have an arbitrary-rank deterministic component as well as a Rayleigh-distributed random component. In particular, it is found that with a non-zero Ricean K-factor, the approximations and the exact uplink rates converge to the same constant value if the number of base station antennas, M, grows large, while the transmit power of each user is scaled down proportionally to 1/M. However, if the channel is Rayleigh fading, we can only cut the transmit power of each user proportionally to 1/√M. In addition, we show that with increasing Ricean K-factor, the uplink rates will converge to fixed values for both MRC and ZF receivers.