Wenjin Wang

Bio: Wenjin Wang is an academic researcher from Southeast University. The author has contributed to research in topics: Precoding & Channel state information. The author has an hindex of 5, co-authored 10 publications receiving 120 citations. Previous affiliations of Wenjin Wang include National and Kapodistrian University of Athens.

Robust Multigroup Multicast Transmission for Frame-Based Multi-Beam Satellite Systems

Abstract: We investigate robust multigroup multicast transmission for frame-based multi-beam satellite communication systems with full frequency reuse. To mitigate the effect of outdated channel state information (CSI), we first investigate robust multigroup multicast precoding that maximizes the minimum average signal to interference plus noise ratio (SINR) under the per-beam power constraints. We show the relationship between the robust max–min fair problem and the robust power minimization problem with partial CSI and propose a low complexity precoder for the robust power minimization problem. We then investigate user clustering which only requires partial CSI. We show that the approximated average SINR can be maximized provided that the estimated channel vectors of the users in the same cluster are linearly dependent while those in different clusters are mutually orthogonal. Motivated by this user clustering condition, we further propose a low-complexity user clustering algorithm. Simulation results demonstrate that the proposed robust approach can provide substantial performance gains over the conventional approach in multi-beam satellite communication systems.

Outage Constrained Robust Multigroup Multicast Beamforming for Multi-Beam Satellite Communication Systems

Abstract: We investigate outage constrained robust multigroup multicast beamforming for multi-beam satellite communication systems with full frequency reuse. Based on a satellite downlink beam domain channel model with channel phase uncertainty taken into account, we first investigate robust multigroup multicast beamforming with the aim to maximize the worst-case outage signal-to-interference-plus-noise ratio under the outage and the per-beam power constraints. We then cast the outage constrained robust beamforming design into the convex optimization framework with some approximation techniques. Simulation results show that the proposed robust multigroup multicast beamformer can provide significant performance gains in terms of multicast rate and outage probability over the conventional approach.

Turbo equalization for LTE uplink under imperfect channel estimation

Abstract: Single-carrier frequency division multiple access (SC-FDMA) has appeared to be a promising technique for high data rate communication in Long Term Evolution (LTE) uplink. In this paper, we propose an improved turbo equalizer for multiuser multiple-input multiple-output (MU-MIMO) LTE uplink to enhance the performance as the channel statement information is imperfect at the receiver. we derive the optimal soft-input soft-output (SISO) detector in turbo equalizer based on minimum mean squre error (MMSE) criterion under imperfect channel estimation by concerning the statistical characteristic of the channel estimation error. It can be implemented in frequency-domain and almostly cause no increase in computational complexity compared to the conventional turbo equalizer for SC-FDMA. Simulation results for LTE scenario demonstrate that the proposed turbo equalizer yields 0.8–1.0dB gain to the turbo receiver which does not consider the imperfect CSI when channel estimation errors exist.

Non-Orthogonal Unicast and Multicast Transmission for Massive MIMO With Statistical Channel State Information

Abstract: We investigate non-orthogonal unicast and multicast (NOUM) transmission for massive multiple-input multiple-output systems, where only statistical channel state information of all user terminals is available at the base station. We adopt a weighted sum of the achievable ergodic unicast rate and multicast rate as the design objective. We first show the closed-form eigenvectors of the optimal unicast and multicast transmit covariance matrices, respectively, which reveals the optimality of beam domain transmission and simplifies the large-dimensional matrix-valued NOUM transmission design into a beam domain power allocation problem. Via invoking the concave-convex procedure, we, then, propose an efficient iterative beam domain power allocation algorithm with guaranteed convergence to a stationary point. In addition, we derive the deterministic equivalent of the objective in each iteration to further reduce the optimization complexity. Simulation results show that the proposed NOUM transmission can provide a significant performance gain in terms of the achievable ergodic unicast-multicast rate region over the conventional orthogonal approach.

Robust Multigroup Multicast Precoding for Frame-Based Multi-Beam Satellite Communications

Abstract: We investigate robust multigroup multicast precoding for frame-based multi-beam satellite communication systems with full frequency reuse. To mitigate the effect of outdated channel state information (CSI), we first investigate robust multigroup multicast precoding that minimizing per beam transmission power while guaranteeing a predetermined average signal to interference plus noise ratio at each user. We then propose a low complexity precoder for it based on semidefinite relaxation and Gaussian randomization techniques. Simulation results demonstrate that the proposed robust approach can provide substantial performance gains over the conventional approach in multibeam satellite communication systems.

Massive Access for 5G and Beyond

Abstract: Massive access, also known as massive connectivity or massive machine-type communication (mMTC), is one of the main use cases of the fifth-generation (5G) and beyond 5G (B5G) wireless networks. A typical application of massive access is the cellular Internet of Things (IoT). Different from conventional human-type communication, massive access aims at realizing efficient and reliable communications for a massive number of IoT devices. Hence, the main characteristics of massive access include low power, massive connectivity, and broad coverage, which require new concepts, theories, and paradigms for the design of next-generation cellular networks. This paper presents a comprehensive survey of massive access design for B5G wireless networks. Specifically, we provide a detailed review of massive access from the perspectives of theory, protocols, techniques, coverage, energy, and security. Furthermore, several future research directions and challenges are identified.

Non-terrestrial networks in 5G & beyond: A survey

Abstract: Fifth-generation (5G) telecommunication systems are expected to meet the world market demands of accessing and delivering services anywhere and anytime. The Non-Terrestrial Network (NTN) systems are able to satisfy the requests of anywhere and anytime connections by offering wide-area coverage and ensuring service availability, continuity, and scalability. In this work, we review the 3GPP NTN features and their potential for satisfying the user expectations in 5G & beyond networks. The state of the art, current 3GPP research activities, and open issues are summarized to highlight the importance of NTN over the wireless communication landscape. Future research directions are also identified to assess the role of NTN in 5G and beyond systems.

Massive Access for 5G and Beyond

Abstract: Massive access, also known as massive connectivity or massive machine-type communication (mMTC), is one of the main use cases of the fifth-generation (5G) and beyond 5G (B5G) wireless networks. A typical application of massive access is the cellular Internet of Things (IoT). Different from conventional human-type communication, massive access aims at realizing efficient and reliable communications for a massive number of IoT devices. Hence, the main characteristics of massive access include low power, massive connectivity, and broad coverage, which require new concepts, theories, and paradigms for the design of next-generation cellular networks. This paper presents a comprehensive survey of aspects of massive access design for B5G wireless networks. Specifically, we provide a detailed review of massive access from the perspectives of theory, protocols, techniques, coverage, energy, and security. Furthermore, several future research directions and challenges are identified.

Massive MIMO Transmission for LEO Satellite Communications

Abstract: 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.