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See detailDownlink Transmit Design in Massive MIMO LEO Satellite Communications
Li, Ke-Xin; You, Li; Want, Jiaheng et al

in IEEE Transactions on Communications (2021)

Low earth orbit (LEO) satellite communication systems have attracted extensive attention due to their smaller pathloss, shorter round-trip delay and lower launch cost compared with geostationary ... [more ▼]

Low earth orbit (LEO) satellite communication systems have attracted extensive attention due to their smaller pathloss, shorter round-trip delay and lower launch cost compared with geostationary counterparts. In this paper, the downlink transmit design for massive multiple-input multiple-output (MIMO) LEO satellite communications is investigated. First, we establish the massive MIMO LEO satellite channel model where the satellite and user terminals (UTs) are both equipped with the uniform planar arrays. Then, the rank of transmit covariance matrix of each UT is shown to be no larger than one to maximize ergodic sum rate, which reveals the optimality of single-stream precoding for each UT. The minorization-maximization algorithm is used to compute the precoding vectors. To reduce the computation complexity, an upper bound of ergodic sum rate is resorted to produce a simplified transmit design, where the rank of optimal transmit covariance matrix of each UT is also shown to not exceed one. To tackle the simplified precoder design, we derive the structure of precoding vectors, and formulate a Lagrange multiplier optimization (LMO) problem building on the structure. Then, a low-complexity algorithm is devised to solve the LMO, which takes much less computation effort. Simulation results verify the performance of proposed approaches. [less ▲]

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See detailMassive MIMO Downlink Transmission for LEO Satellite Communications
Li, Ke-Xin; You, Li; Wang, Jiaheng et al

Poster (2021, September)

We investigate the downlink (DL) transmit strategy for massive multiple-input multiple-output (MIMO) low-earthorbit (LEO) satellite communication (SATCOM) systems, in which only the slow-varying ... [more ▼]

We investigate the downlink (DL) transmit strategy for massive multiple-input multiple-output (MIMO) low-earthorbit (LEO) satellite communication (SATCOM) systems, in which only the slow-varying statistical channel state information is known at the transmitter side. First, we establish the massive MIMO LEO satellite channel model, in which the uniform planar arrays are deployed at both the satellite and user terminals (UTs). Building on the rank-one property of satellite channel matrices, we show that transmitting a single data stream to each UT is optimal for the ergodic sum rate maximization. This result is of great importance for massive MIMO LEO SATCOM systems, since the sophisticated design of transmit covariance matrices is turned into that of precoding vectors, with no loss of optimality at all. Furthermore, we conceive an algorithm to compute the precoding vectors. Simulation results show the significant performance gains of the proposed approaches over the previous schemes. [less ▲]

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See detailHybrid A/D Precoding for Downlink Massive MIMO in LEO Satellite Communications
Qiang, Xiaoyu; You, Li; Li, Ke-Xin et al

in 2021 IEEE International Conference on Communications Workshops (ICC Workshops) (2021, July 09)

In this paper, we develop hybrid analog/digital precoding based on the fully-connected architecture for massive multiple-input multiple-output (MIMO) low earth orbit (LEO) satellite communications (SATCOM ... [more ▼]

In this paper, we develop hybrid analog/digital precoding based on the fully-connected architecture for massive multiple-input multiple-output (MIMO) low earth orbit (LEO) satellite communications (SATCOM), by exploiting the statistical channel state information (CSI) at the transmitter. The hybrid precoder design is formulated as an energy efficiency (EE) maximization problem by considering both continuous and discrete phase shift networks for implementing the analog precoder. The resulting optimization problem is nonconvex and difficult to solve. To that end, first, we apply a closed-form tight upper bound to approximate the ergodic rate. Then, we adopt Dinkelbach's algorithm and the iteratively weighted minimum mean-square error (WMMSE) method to obtain the fully digital precoders. After that, the alternating minimization and inexact majorization-minimization (MM) algorithms are utilized to compute the hybrid precoders. Simulation results show that the proposed algorithmic solutions achieve significant performance gains when compared to existing literature ones, especially in the case where the discrete phase shift network is employed for analog precoding. [less ▲]

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