Low earth orbit (LEO) satellite communications are expected to be incorporated in future wireless networks, in particular 5G and beyond networks, to provide global wireless access with enhanced data rates. Massive multiple-input multiple-output (MIMO) techniques, though widely used in terrestrial communication systems, have not been applied to LEO satellite communication systems. In this paper, we propose a massive MIMO transmission scheme with full frequency reuse (FFR) for LEO satellite communication systems and exploit statistical channel state information (sCSI) to address the difficulty of obtaining instantaneous CSI (iCSI) at the transmitter. We first establish the massive MIMO channel model for LEO satellite communications and simplify the transmission designs via performing Doppler and delay compensations at user terminals (UTs). Then, we develop the low-complexity sCSI based downlink (DL) precoder and uplink (UL) receiver in closed-form, aiming to maximize the average signal-to-leakage-plus-noise ratio (ASLNR) and the average signal-to-interference-plus-noise ratio (ASINR), respectively. It is shown that the DL ASLNRs and UL ASINRs of all UTs reach their upper bounds under some channel condition. Motivated by this, we propose a space angle based user grouping (SAUG) algorithm to schedule the served UTs into different groups, where each group of UTs use the same time and frequency resource. The proposed algorithm is asymptotically optimal in the sense that the lower and upper bounds of the achievable rate coincide when the number of satellite antennas or UT groups is sufficiently large. Numerical results demonstrate that the proposed massive MIMO transmission scheme with FFR significantly enhances the data rate of LEO satellite communication systems. Notably, the proposed sCSI based precoder and receiver achieve the similar performance with the iCSI based ones that are often infeasible in practice.

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Massive MIMO Transmission for LEO Satellite Communications

We propose a new hybrid precoding technique for massive multi-input multi-output (MIMO) systems using spatial channel covariance matrices in the analog precoder design. Applying a regularized zero-forcing precoder for the baseband precoding matrix, we find an unconstrained analog precoder that maximizes signal-to-leakage-plus-noise ratio (SLNR) while ignoring analog phase shifter constraints. Subsequently, we develop a technique to design a constrained analog precoder that mimics the obtained unconstrained analog precoder under phase shifter constraints. The main idea is to adopt an additional baseband precoding matrix, which we call a compensation matrix. We analyze the SLNR loss due to the proposed hybrid precoding compared to fully digital precoding, and determine which factors have a significant impact on this loss. In the simulations, we show that if the channel is spatially correlated and the number of users is smaller than the number of RF chains, the SLNR loss becomes negligible compared to fully digital precoding. The main benefit of our method stems from the use of spatial channel matrices in such a way that not only is each user's desired signal considered, but also the inter-user interference is incorporated in the analog precoder design.

Exploiting Spatial Channel Covariance for Hybrid Precoding in Massive MIMO Systems

Precoding has been conventionally considered as an effective means of mitigating or exploiting the interference in the multiantenna downlink channel, where multiple users are simultaneously served with independent information over the same channel resources. The early works in this area were focused on transmitting an individual information stream to each user by constructing weighted linear combinations of symbol blocks (codewords). However, more recent works have moved beyond this traditional view by: 1) transmitting distinct data streams to groups of users and 2) applying precoding on a symbol-per-symbol basis. In this context, the current survey presents a unified view and classification of precoding techniques with respect to two main axes: 1) the switching rate of the precoding weights, leading to the classes of block-level and symbol-level precoding and 2) the number of users that each stream is addressed to, hence unicast, multicast, and broadcast precoding. Furthermore, the classified techniques are compared through representative numerical results to demonstrate their relative performance and uncover fundamental insights. Finally, a list of open theoretical problems and practical challenges are presented to inspire further research in this area 1 . 1 The concepts of precoding and beamforming are used interchangeably throughout this paper.

/pdf/symbol-level-and-multicast-precoding-for-multiuser-19itwisvs4.pdf

Symbol-Level and Multicast Precoding for Multiuser Multiantenna Downlink: A State-of-the-Art, Classification, and Challenges

Low earth orbit (LEO) satellite communications are expected to be incorporated in future wireless networks, in particular 5G and beyond networks, to provide global wireless access with enhanced data rates. Massive MIMO techniques, though widely used in terrestrial communication systems, have not been applied to LEO satellite communication systems. In this paper, we propose a massive MIMO transmission scheme with full frequency reuse (FFR) for LEO satellite communication systems and exploit statistical channel state information (sCSI) to address the difficulty of obtaining instantaneous CSI (iCSI) at the transmitter. We first establish the massive MIMO channel model for LEO satellite communications and simplify the transmission designs via performing Doppler and delay compensations at user terminals (UTs). Then, we develop the low-complexity sCSI based downlink (DL) precoder and uplink (UL) receiver in closed-form, aiming to maximize the average signal-to-leakage-plus-noise ratio (ASLNR) and the average signal-to-interference-plus-noise ratio (ASINR), respectively. It is shown that the DL ASLNRs and UL ASINRs of all UTs reach their upper bounds under some channel condition. Motivated by this, we propose a space angle based user grouping (SAUG) algorithm to schedule the served UTs into different groups, where each group of UTs use the same time and frequency resource. The proposed algorithm is asymptotically optimal in the sense that the lower and upper bounds of the achievable rate coincide when the number of satellite antennas or UT groups is sufficiently large. Numerical results demonstrate that the proposed massive MIMO transmission scheme with FFR significantly enhances the data rate of LEO satellite communication systems. Notably, the proposed sCSI based precoder and receiver achieve the similar performance with the iCSI based ones that are often infeasible in practice.

/pdf/massive-mimo-transmission-for-leo-satellite-communications-2hzkmfvhz2.pdf

This paper provides an overview of multi-cell coordinated scheduling and multiple-input multiple-output (MIMO) techniques in LTE. We first discuss single-user MIMO (SU-MIMO) and multi-user MIMO (MU-MIMO) for LTE and identify potential techniques for further improving the performance of LTE, such as enhanced channel state information feedback and adaptive switching between SU-MIMO and MU-MIMO. Then, we address inter-cell interference mitigation techniques for downlink and uplink, respectively. Finally, potential research challenges and topics in the area are discussed.

Multi-Cell Coordinated Scheduling and MIMO in LTE

This letter considers transmit precoding schemes based on the maximum signal-to-leakage-and-noise ratio (SLNR) in multiuser MIMO systems with single-antenna receivers. The closed-form solution of SLNR design is generally given in the form of the eigenvector associated to the maximum eigenvalue. In this letter, analytic expressions of SLNR-based solutions and resulting SLNR are derived for a generic power allocation (GPA). The solution is shown to be a function of user-allocated power and an arbitrary phase shift. Under equal power allocation (EPA), the SLNR precoding scheme is shown to be equivalent to the minimum mean square error (MMSE) precoding scheme. Several useful implications in terms of the possible extension of existing algorithms and performance analysis are also discussed.

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On the Equivalence Between SLNR and MMSE Precoding Schemes with Single-Antenna Receivers

This paper proposes a linear transmit filter design to maximize weighted sum capacity (WSC) in multiuser multiple-input–multiple-output (MU-MIMO) systems. The proposed scheme is based on a modified signal-to-leakage-plus-noise ratio (SLNR) criterion, which integrates receiver structures and power allocations into the precoder design and can efficiently exploit unused receiver subspaces. Based on the proposed transmitter (TX) design with receive matched filters (MFs), the WSC maximization problem can be simplified to power-allocation and data-stream selection problems. A power-allocation algorithm for finding a local optimal solution is also proposed and is shown to be obtained by the iteration of closed-form water-filling (WF) solutions. Furthermore, a low-complexity user and substream selection is proposed as an alternative solution to maximize WSC. Simulation results show that the proposed algorithms outperform the conventional scheme and achieve comparable performance to a joint transceiver design, despite requiring simpler receiver structures.

/pdf/weighted-sum-capacity-maximization-using-a-modified-leakage-5e8gna353t.pdf

Weighted Sum Capacity Maximization Using a Modified Leakage-Based Transmit Filter Design

In this letter, equivalent expressions of transmit precoding solutions based on the maximum signal-to-leakage-plus-noise ratio (SLNR) are derived for multiuser MIMO systems with multi-antenna receivers. The performance of the SLNR precoding scheme is also analysed based on this equivalent form. Further, it is shown that the SLNR scheme can be viewed as a generalised channel regularisation technique and the conditions for an equivalence between the SLNR, the Regularised Block Diagonalisation (RBD) and the Generalised MMSE Channel Inversion (GMI method 2) schemes are given. Consequently, the performance analysis in this letter can be extended to the RBD and GMI schemes. This generalises the equivalence between the SLNR and MMSE schemes and its useful implications, from the case of single-antenna to multi-antenna receivers.

/pdf/equivalent-expressions-and-performance-analysis-of-slnr-5ly58tx5f7.pdf

Equivalent Expressions and Performance Analysis of SLNR Precoding Schemes: A Generalisation to Multi-Antenna Receivers

This paper investigates the user scheduling strategy of multi-user MIMO (MU-MIMO) systems using a transmit precoding scheme based on maximum signal to leakage and noise ratio (SLNR). When users are equipped with multiple antennas, joint user and receive antenna selection may be performed and is shown to potentially provide superior performance to user selection schemes where users utilise all available antennas, especially at high SNR. To overcome the impractical computational burden of exhaustive methods, two suboptimal algorithms are presented in this paper. The simulation results show that the proposed suboptimal algorithms perform very close to the exhaustive joint user and antenna selection algorithm.

Reduced Complexity Joint User and Receive Antenna Selection Algorithms for SLNR-Based Precoding in MU-MIMO Systems

In this study, linear transceiver designs are proposed based on modified definitions of signal-to-leakage-plus-noise ratio (mSLNR) for multi-cell coordinated beamforming scenarios. Two mSLNR definitions are presented, one of which modifies the computation of leakage and noise powers, while the other applies the modified procedure to the desired power calculation in addition to the computation of leakage and noise powers. The proposed mSLNRs are generally valid for any receiver types. Various linear receivers are studied, several of which, when applied with the first mSLNR definition, are shown to be equivalent. Moreover, a special case of the proposed scheme is shown to be equivalent to an existing algorithm. Iterative precoding algorithms are also presented with a discussion on their convergence properties. The proposed transceiver designs are further extended to incorporate scheduling functionalities. A weighted sum rate maximisation problem is formulated and is solved by two separate approaches, namely power allocation and data-substream selection methods. Simulation results show that, for multiple users per cell, the proposed algorithms can effectively integrate user and substream selections and achieve multi-user diversity gain.

Piya Patcharamaneepakorn

Papers

On the Equivalence Between SLNR and MMSE Precoding Schemes with Single-Antenna Receivers

Weighted Sum Capacity Maximization Using a Modified Leakage-Based Transmit Filter Design

Equivalent Expressions and Performance Analysis of SLNR Precoding Schemes: A Generalisation to Multi-Antenna Receivers

Reduced Complexity Joint User and Receive Antenna Selection Algorithms for SLNR-Based Precoding in MU-MIMO Systems

Coordinated beamforming schemes based on modified signal-to-leakage-plus-noise ratio precoding designs