Distributed MIMO Systems Research Articles

Energy-Efficient Optimization via Joint Power and Subcarrier Allocation for eMBB and URLLC Services

This letter considers joint subcarrier and power allocation in the distributed MIMO system for enhanced mobile broadband (eMBB) and ultra-reliable low-latency communication (URLLC) services. Orthogonal and non-orthogonal scheduling scheme can be selected by subcarrier assignment to improve spectral efficiency and meet the reliability requirement of URLLC. Short packet transmission is adopted for URLLC to meet the low latency requirements. We formulate a mixed-integer optimization problem by maximizing the energy efficiency (EE) of the system subject to quality of service (QoS) constraints. The problem is intractable to solve and then we propose a low computational complexity algorithm to find the suboptimal solution of the problem. Simulation results show that the proposed algorithm can converge fast and significantly improve the EE for eMBB and URLLC services.

Joint User Scheduling and Resource Allocation in Distributed MIMO Systems with Multi-Carriers

Compared with the traditional collocated multi-input multi-output system (C-MIMO), distributed MIMO (D-MIMO) systems have the advantage of higher throughput and coverage, making them strong candidates for next-generation communication architecture. As a practical implementation of a D-MIMO cooperative network, the multi-TRP (multiple transmission/reception point) system becomes a hotspot in the research of advanced 5G. Different from previous research on a cooperative D-MIMO network with single narrowband transmission, this paper proposes a joint optimization scheme to address the user scheduling problem along with carrier allocation to maximize the total spectral efficiency (SE) in the downlink of coherent multi-TRP systems with multi-carriers. We establish a joint optimization model of user scheduling and resource allocation to maximize the system spectral efficiency under the constraints of power consumption and the backhaul capacity limits at each RAU (remote antenna unit), as well as the QoS (quality of service) requirement at each user. Since the optimization model is both non-covex and non-smooth, a joint optimization algorithm is proposed to solve this non-convex combinatorial optimization problem. We first smooth the mixed-integer problem by employing penalty functions, and after decoupling the coupled variables by introducing auxiliary variables, the original problem is transformed into a series of tractable convex optimization problems by using successive convex approximation (SCA). Numerical results demonstrate that the proposed joint optimization algorithm for user scheduling and resource allocation can reliably converge and achieve a higher system SE than the general multi-TRP system without carrier allocation, and this advantage is more pronounced under a higher backhaul capacity or higher power consumption constraints.

Lower bound on the capacity of distributed MIMO systems with spatially correlated Rician/Lognormal fading

This paper presents an analytic lower bound of ergodic capacity for distributed MIMO (D-MIMO) systems that experience not only Rician fading but also shadowing effects of Lognormal distributed. In particularly, we consider that the Rician fading channel is spatially correlated at both transmitter and receiver. In the communication environment corresponding to this setting, the angle spread at the transmitter and the angle spread at the receiver are both insufficient, and the non-fading components co-exists with the fading components. Such communication environment is very common. In the process of deriving the analytic lower bound, in order to avoid Hayakawa polynomials that cannot be analytically expressed, non-central quadratic forms are transformed to non-central Wishart matrices by use of inequality. The validity of the presented lower bound is verified by computer simulations. The simulation results show the influence of the number of radio ports at the transmitter, the number of antennas at the transmitter or receiver, correlation level (angle spreads) and Rician K-factor on the capacity of systems. In all cases, the presented bound remains tight across the entire signal-to-noise ratio (SNR) regime.

Distributed MIMO System Design and Channel Capacity Analysis Based on Polar Orbit LEO Constellation

Distributed MIMO System Design and Channel Capacity Analysis Based on Polar Orbit LEO Constellation

Joint Power Allocation and Beamforming for Energy-Efficient Design in Multiuser Distributed MIMO Systems

Energy efficiency (EE) optimization of joint power allocation (PA) and beamforming (BF) is studied for multiuser distributed multiple-input multiple-output (D-MIMO) systems with maximum ratio combining. Subject to power budget constraints, a non-convex constrained optimization problem is firstly formulated to maximize EE of single-user D-MIMO. We propose a near-optimal joint design scheme with the block coordinate descent method, which has an effective iterative algorithm to find optimal BF for fixed PA, and an iterative algorithm based on the Dinkelbach methods to find optimal PA for fixed BF. We also develop a low-complexity suboptimal joint scheme, which has closed-form BF and PA by maximizing an effective signal-to-noise ratio for fixed PA and a derived EE upper bound for fixed BF, respectively. It has lower complexity than the near-optimal scheme with slight performance loss. With these results, two joint design schemes are developed for multiuser D-MIMO. The first scheme can achieve the best performance, while the second one based on closed-form PA and BF has slight performance loss in comparing to that of the former, but with lower complexity. Simulation results verify the effectiveness of the developed schemes over some existing schemes.

Multiobjective Optimization for Resource Allocation in Full-duplex Large Distributed MIMO Systems

Multiobjective Optimization for Resource Allocation in Full-duplex Large Distributed MIMO Systems

Power Allocation for Energy Efficient Optimization of Distributed MIMO System With Beamforming

This paper presents three energy-efficient power allocation (PA) schemes for the downlink of a distributed multiple-input multiple-output (D-MIMO) system with beamforming at distributed antenna ports and antenna selection (AS) at a mobile station over composite Rayleigh channels. Subject to maximum power constraints, a constrained maximization problem on energy efficiency (EE) is formulated. Based on theoretical analysis, the optimal beamforming is shown to be aligned with the channel direction that renders the joint design problem to be a PA optimization one. It is shown that the optimization problem is strictly pseudo-concave with a unique maximum. Thus, an optimal PA scheme based on a gradient projection method is proposed to obtain the global solution. To speed up the gradient projection method, a closed-form initialization is derived. Furthermore, a low-complexity optimal PA schemes based on the Karush–Kuhn–Tucker conditions is proposed. This optimal scheme has a closed-form PA expression for a certain condition or else computes the PA by the Lambert function or the bisection method, and gives the same EE performance as that of the optimal gradient-based scheme. The performances of these two optimal schemes are optimal and verified to be valid in contrast to the inaccurate optimal scheme in the literature. For large maximum power, the closed-form initial PA will become the optimal solution and can be considered as a suboptimal solution with no iterative computation. Making use of the tight upper and lower bounds of the Lambert function, a very low-complexity suboptimal PA scheme is developed. Simulation results show that the proposed suboptimal scheme can achieve nearly optimal performance. Maximum EE and maximum channel power, which are optimal and suboptimal criteria, are adopted for antenna selection. The simple suboptimal criterion can provide EE performance very close to that of the optimal one. The D-MIMO with AS is shown to give considerable EE gain over the single receive antenna system. Moreover, the proposed three PA schemes can be used for multiuser diversity D-MIMO systems to achieve superior EE performance.

Analysis of a distributed MIMO channel capacity under a special scenario

A distributed antenna system enhances the coverage performance of a system by distributing the antennas geographically, as well as by improving the diversity gain and capacity performance. The channel impulse response matrix of a distributed MIMO system in an airplane cabin environment is measured by a self-built channel measurement platform. The transmitting antennas are distributed, and the receiving antennas are placed centrally. The data analysis shows that the distributed MIMO system can significantly increase the system’s channel capacity. The system’s capacity is also closely related to whether the antennas are evenly placed. When the antennas are evenly placed, the capacity is increased and the distribution is more uniform.

On the Performance of Distributed MIMO With Full-Duplex Jamming

In this paper, we consider a distributed MIMO system with a set of geographically distributed nodes forming a multi-antenna source $S$ , and a set of geographically distributed full duplex (FD) nodes forming a multi-antenna destination $D$ . $S$ and $D$ each forms a transmit and a receive cluster, respectively. $D$ uses FD mode to jam the signal from $S$ at eavesdropper $E$ , incurring some residual self-interference. We assume that neither $S$ nor $D$ has knowledge of their instantaneous channel state information to $E$ . Furthermore, to simplify the system design, especially for the mobile case, we assume as well that $S$ has no knowledge of the ICSI of its channel to $D$ . Hence, adopting ergodic secrecy rate (ESR) as the performance metric, we are interested in evaluating the ESR averaged over the nodes’ locations, i.e., cluster averaged ESR. To accomplish this, we obtain a lower bound (LB) and an upper bound of the ESR. As part of our work, we also obtain bounds on the cluster averaged ergodic rate between the two clusters. We demonstrate by simulations that the LB can act as a good approximation of the ESR for practical purposes.

Generalized Signal-Space Alignment Based Physical-Layer Network Coding for Distributed MIMO Systems

We study an uplink distributed multiple-input-multiple-output (D-MIMO) system, where multiple users are served by multiple base stations (BSs) connected to a common central unit (CU). We propose a generalized signal-space alignment (SSA)-based physical-layer network coding (PNC) scheme, termed G-SSA-PNC. In G-SSA-PNC, the multi-antenna users encode their messages by using nested lattice coding, linearly precode the nested lattice codewords for SSA, and then broadcast to the multi-antenna BSs. The BSs linearly post-process the received signals to extract signals at certain aligned directions. PNC decoding is applied to those extracted signals to generate network-coded message combinations, and the decoded message combinations are then forwarded to the CU for user messages decoding. Compared with the original SSA-PNC scheme, our scheme is different in the following three aspects. First, the G-SSA-PNC employs an individual shaping lattice for nested lattice coding at each source, as in contrast to the use of a common shaping lattice in original SSA-PNC. Second, we derive the feasibility condition of PNC decoding under the new nested lattice coding scheme and show that the SSA precoding and the nested lattice coding needs to be jointly designed to meet the feasibility condition. Third, we formulate a sum rate maximization problem and propose a suboptimal solution to the problem. The numerical results demonstrate the superiority of the G-SSA-PNC in performance over the benchmark schemes, including original SSA-PNC, compress-and-forward, and interference alignment.

Sum Rate Analysis for Precoder Design in Distributed MIMO Systems Over Composite Fading Channels

In this paper, we consider the distributed multiple-input multiple-output systems which experience both the small-scale and large-scale fading. By employing the Rayleigh-lognormal model to characterize the composite fading channels, we derive the uplink sum rate in terms of the signal-to-noise ratio for zero forcing (ZF) and ZF decision feedback receivers, respectively. Afterwards, we propose an optimal power loading strategy by constructing an optimization problem that maximizes the dominant term of the sum rate. Then on this basis, a two-stage precoder is designed to further improve the performance, where only the first and second order statistics of the channels are needed at the transmitters. Numerical simulations testify the effectiveness of the analytical sum rates and present the superiority of our optimal power loading strategy as well as the two-stage precoder.

An Interference Cancellation Technique for Distributed MIMO Systems

This study proposes an uncooperative-multi-cell-multiple-input–multiple-output system to increase the throughput of an ill-conditioned wireless MIMO downlink system. The proposed algorithm suppresses the inter-cell interference at each mobile station using a set of adaptive receive beamformers, but handles the intra-cell interference at each base station using a Tomlinson Harashima precoder. Using the singular vectors of channel matrices, the receive beamformers can be designed based on a linear-constrained-minimum-variance criterion. On the other hand, to obtain high enough degree of freedoms for cancelling the intra-cell interference at each base station, the precoder is applied to the re-assembled downlink virtual channel formed by the simplified channel state information. Using the proposed interference suppression techniques, a multi-cell downlink system with multiple uncooperative base stations can be decomposed into a set of parallel subchannels. The resulting system has better performance in channel capacity than conventional MIMO systems. Computer simulations support the validity of the proposed approach.

Reciprocity Calibration for Massive MIMO: Proposal, Modeling, and Validation

This paper presents a mutual coupling-based calibration method for time-division-duplex massive MIMO systems, which enables downlink precoding based on uplink channel estimates. The entire calibration procedure is carried out solely at the base station (BS) side by sounding all BS antenna pairs. An expectation-maximization (EM) algorithm is derived, which processes the measured channels in order to estimate calibration coefficients. The EM algorithm outperforms the current state-of-the-art narrow-band calibration schemes in a mean squared error and sum-rate capacity sense. Like its predecessors, the EM algorithm is general in the sense that it is not only suitable to calibrate a co-located massive MIMO BS, but also very suitable for calibrating multiple BSs in distributed MIMO systems. The proposed method is validated with experimental evidence obtained from a massive MIMO testbed. In addition, we address the estimated narrow-band calibration coefficients as a stochastic process across frequency, and study the subspace of this process based on measurement data. With the insights of this study, we propose an estimator which exploits the structure of the process in order to reduce the calibration error across frequency. A model for the calibration error is also proposed based on the asymptotic properties of the estimator, and is validated with measurement results.

Achievable uplink rate analysis for distributed massive MIMO systems with interference from adjacent cells

This work focuses on the multi-cell multi-user distributed massive MIMO (DM-MIMO) systems, of which each user is equipped with single antenna and the base stations (BSs) consists of distributed antenna units. We first investigate the arbitrary BS antenna topology scenario. The derivation indicates that in this case the achievable uplink rate of an arbitrary user in central cell depends on both the number of BS's antennas and the users' access distance to each distributed antenna unit (DAU). As a result, the performance analysis based on the derivations is difficult. To overcome this issue and achieve clearer insight, we then consider a circularly distributed BS antenna array and obtain the asymptotic uplink rate of an arbitrary user by considering the asymptotic case where the number of antennas of BSs tends to infinity. It is achieved that the asymptotic uplink rate only depends on the distance from users' position to the center of reference cell. The presented numerical results show clearly that the distributed massive MIMO systems outperform the centralized ones. Moreover, it is also achieved that the interference from the adjacent cells imposes great impact on system performance. Besides this, in numerical analysis the average asymptotic uplink rate of a user is presented, which is free of the users' position and only depends on the radius of circular antenna arrays. It is achieved the maximum average uplink rate would be achieved when the radius of circularly distributed antenna array goes to its optimization location.

Pilot power adaptation for tomographic channel estimation in distributed MIMO systems

In distributed multiple-input multiple-output (D-MIMO) systems, the improvements of spectral and energy efficiencies rely heavily on the accuracy of the channel state information (CSI). In order to enhance the accuracy of CSI acquisition, the problem of pilot design in a D-MIMO system is addressed in this study. In particular, the authors focus on the optimisation of pilot power adaptation in a single-cell D-MIMO system with multiple users served in orthogonal resources. Under the concept of tomographic channel estimation, the problem of pilot power adaptation aiming at maximising the lower bound of the sum capacity is formulated. As the computational complexity of solving the problem is relatively high due to the mutual coupling constraints, the dual decomposition technique is introduced to decouple the constraints and reduce the complexity via parallel computation. An effective pilot power adaptation scheme is further proposed by using the projected subgradient method. The superiority and effectiveness of the proposed scheme are illustrated by the simulation results.

CMOS Integrated Remote Antenna Unit for Fiber-Fed Distributed MIMO Systems

A fully integrated remote antenna unit (RAU) intended for fiber-fed distributed multiple-input multiple-output systems is presented. The circuit is designed for narrowband (60 MHz) time-division duplex systems, where an IF over fiber approach is chosen to facilitate the use of low-cost optical components and integrated photodetectors. A novel antenna switch control scheme is introduced, which enables the use of an integrated antenna switch instead of a bulky off chip circulator. The reference frequency signal is distributed in the fiber together with user data and used by a phase-locked-loop-based frequency synthesizer to generate the local oscillator signal inside the RAU, hence synchronizing all RAUs of the distributed antenna system. At an operating frequency of 2.1 GHz, the measured optical-to-electrical conversion gain of the downlink is 71.7 dB, the error vector magnitude is 3.2%, and the adjacent channel leakage ratio is 39.2 dBc at an output power of +3 dBm for a 16-quadrature amplitude modulation (16-QAM) long-term evolution downlink signal. The uplink has a gain of 32.5 dB, a noise figure of 3.5 dB, and an in-band third-order intercept point of -12 dBm. Implemented in a standard 65-nm CMOS process, the complete RAU occupies just 2 mm <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sup> of die area and consumes 146 mW during downlink signal transmission and 122 mW during uplink signal reception.

Distributed MIMO Broadcasting: Reverse Compute-and-Forward and Signal-Space Alignment

We study a downlink distributed MIMO system where a central unit (CU) broadcasts messages to $K^{\prime }$ users through $K$ distributed BSs. The CU is connected to the BSs via $K$ independent rate-constrained fronthaul (FH) links. The distributed BSs collectively serve the users through the air. We propose a new network coding based distributed MIMO broadcasting scheme, using reverse compute-and-forward and signal-space alignment. At the CU, a network coding generator matrix is employed for pre network coding of the users’ messages. The network coded messages are forwarded to the BSs, where the FH rate-constraint determines the actual number of network-coded messages forwarded to the BSs. At the BSs, linear precoding matrices are designed to create a number of bins , each containing a bunch of spatial streams with aligned signal-spaces. At each user, post physical-layer network coding is employed to compute linear combinations over the NC messages with respect to the bins, which reverses the prenetwork coding and recovers the desired messages. We derive an achievable rate of the proposed scheme based on the existence of NC generator matrix, signal-space alignment precoding matrices, and nested lattice codes. Improved rate and degrees of freedom over existing interference alignment and compress-and-forward schemes are shown. Numerical results demonstrate the performance improvement, e.g., by as much as 70% increase in throughput over benchmark schemes.

Energy Efficient Power Allocation for Distributed MIMO System

The rapid increasing demands of multi-media applications have busted the improvement of video transmission. By the increase of multimedia transmission, quality of experience (QoE) has become the hot topic of the wireless networks’ research. This paper proposes a QoE-aware resource allocation algorithm in MIMO-OFDM Networks. The power allocation estimation is formulated to maximize according to QoE by considering the video transmission rate and the subcarrier schemes under the constraint of minimum power. In this paper, we will analyses the the performance of video transmission from transmission rate at the application layer to the power allocation at the physical layer. From simulation results, we can see that the proposed subcarrier allocation algorithm maximizes the video QoE by minimizing the sum distortion of multi-users in MIMO networks with power constraints.

3D nested distributed massive MIMO: Modeling and performance analysis

The Large Scale Multiple-input-multiple-output (MIMO) system, also called Massive MIMO in past researches, are considering the azimuth angle only. However, in a 3D distributed antenna system, the elevation angle cannot be ignored. Nested array as a two dimensional arrays was firstly proposed to perform array processing with increased degree of freedom, using less number of sensors at the same time. This paper introduces a novel 3D MIMO antenna deployment based on nested co-array. As the difference co-arrays are invariance, in the 3D nested distributed MIMO system, we are able to calculate the covariance matrix of channels. Based on this inference, we model a 3D nested distributed MIMO system and analyze its performance with achievable sum rate. By applying the nested deployment, our proposed method could achieve a Massive MIMO with less number of physical antennas. Numerical results also provided to support our model.

Optimal Diagonal Power Loading Minimizing Asymptotic Symbol Error Probability for Distributed MIMO Systems With ZF Receivers

In this paper, we consider a distributed multiple-input–multiple-output (D-MIMO) system, where the channel is flat fading and may be correlated, and experiences both small- and large-scale fading. We assume that full knowledge of channel state information (CSI) is available at the receiver and that only the first-and second-order statistics of the channel are available at the transmitter. For such a system with square quadrature amplitude modulation (QAM), an asymptotic symbol error probability (SEP) is derived for the linear zero-forcing (ZF) receiver. Then, we propose an optimal diagonal power loading (PL) strategy that minimizes the dominant term of the asymptotic SEP subject to either a total transmission power constraint when the total power normalization coefficient can be fed back to the transmitter from the receiver or an individual transmission power constraint. A simple closed-form solution is obtained. Computer simulations show that our presented optimal system attains significant performance gains over the currently available equal PL system.