Cunhua Pan

Large-Scale Antenna Systems With UL/DL Hardware Mismatch: Achievable Rates Analysis and Calibration

This paper studies the impact of hardware mismatch (11M) between the base station (BS) and the user equipment (UE) in the downlink (DL) of large-scale antenna systems. Analytical expressions to predict the achievable rates are derived for different precoding methods, i.e., matched filter (MF) and regularized zero-forcing (RZF), using large system analysis techniques. Furthermore, the upper bounds on achievable rates of MF and RZF with 11M are investigated, which are related to the statistics of the circuit gains of the mismatched hardware. Moreover, we present a study of 11M calibration, where we take zero-forcing (ZF) precoding as an example to compare two 11M calibration schemes, i.e., Pre-precoding Calibration (Pre-Cal) and Post-precoding Calibration (Post-Cal). The analysis shows that Pre-Cal outperforms Post-Cal schemes. Monte-Carlo simulations are carried out, and numerical results demonstrate the correctness of the analysis.

Joint Precoding and RRH Selection for User-Centric Green MIMO C-RAN

This paper jointly optimizes the precoding matrices and the set of active remote radio heads (RRHs) to minimize the network power consumption for a user-centric cloud radio access network, where both the RRHs and users have multiple antennas and each user is served by its nearby RRHs. Both users’ rate requirements and per-RRH power constraints are considered. Due to these conflicting constraints, this optimization problem may be infeasible. In this paper, we propose to solve this problem in two stages. In Stage I, a low-complexity user selection algorithm is proposed to find the largest subset of feasible users. In Stage II, a low-complexity algorithm is proposed to solve the optimization problem with the users selected from Stage I. Specifically, the re-weighted

Totally distributed energy-efficient transmission design in MIMO interference channels

l_{1}

Weighted Sum Energy Efficiency Maximization in Ad Hoc Networks

-norm minimization method is used to transform the original problem with non-smooth objective function into a series of weighted power minimization (WPM) problems, each of which can be solved by the weighted minimum mean square error (WMMSE) method. The solution obtained by the WMMSE method is proved to satisfy the Karush-Kuhn-Tucker conditions of the WPM problem. Moreover, a low-complexity algorithm based on Newton’s method and the gradient descent method is developed to update the precoder matrices in each iteration of the WMMSE method. Simulation results demonstrate the rapid convergence of the proposed algorithms and the benefits of equipping multiple antennas at the user side. Moreover, the proposed algorithm is shown to achieve near-optimal performance in terms of NPC.

On consideration of content preference and sharing willingness in D2D assisted offloading

In this paper, we consider the problem of maximizing the energy efficiency (EE) for multiple-input-multiple-output (MIMO) interference channels (ICs), subject to the per-link power constraint. To avoid extensive information exchange among all links, the optimization problem is formulated as a noncooperative game, where each link maximizes its own EE. We show that this game always admits a Nash equilibrium (NE) and the sufficient condition for the uniqueness of the NE is derived for the case of large enough maximum transmit power constraint. To reach the NE of this game, we develop a totally distributed EE algorithm, in which each link updates its own transmit covariance matrix in a completely distributed and asynchronous way. Some players may update their solutions more frequently than others or even use the outdated interference information. The sufficient conditions that guarantee the global convergence of the proposed algorithm to the NE of the game have been given as well. We also study the impact of the circuit power consumption on the sum EE performance of the proposed algorithm in the case when the links are separated sufficiently far away. Moreover, the tradeoff between the sum EE and the sum spectral efficiency (SE) is investigated with the proposed algorithm under two special cases: 1) low transmit power constraint regime; and 2) high transmit power constraint regime. Finally, extensive simulations are conducted to evaluate the impact of various system parameters on the system performance.

Power Minimization in Multi-Band Multi-Antenna Cognitive Radio Networks

In this letter, we propose a distributed adaptive-pricing algorithm aimed at solving the weighted sum energy efficiency (EE) maximization problem in ad hoc networks. It is theoretically proven that the proposed distributed algorithm strictly converges to the Karush-Kuhn-Tucker (KKT) point of the problem. Significant performance enhancement is observed by numerical results with fast convergence. Moreover, it is shown that the proposed algorithm degrades gracefully when decreasing overhead of information exchange.

Energy Efficiency Optimization for MIMO Distributed Antenna Systems

Device-to-device (D2D) assisted offloading heavily depends on the participation of human users. The content preference and sharing willingness of human users are two crucial factors in the D2D assisted offloading. In this paper, with consideration of these two factors, the optimal content pushing strategy is investigated by formulating an optimization problem to maximize the offloading gain measured by the offloaded traffic. Users are placed into groups according to their content preferences and share content with intergroup and intragroup users at different sharing probabilities. Although the optimization problem is nonconvex, the closed-form optimal solution for a special case is obtained, when the sharing probabilities for intergroup and intragroup users are the same. Furthermore, an alternative group optimization (AGO) algorithm is proposed to solve the general case of the optimization problem. Finally, simulation results are provided to demonstrate the offloading performance achieved by the optimal pushing strategy for the special case and AGO algorithm. An interesting conclusion drawn is that the group with the largest number of interested users is not necessarily given the highest pushing probability. It is more important to give high pushing probability to users with high sharing willingness.

Mapping Codebook-Based Physical Network Coding for Asymmetric Two-Way Relay Channels

This paper aims to design an optimal set of beam-vectors for multi-band multi-antenna cognitive radio networks that jointly allocate power over both space and frequency, so that the sum power of secondary users (SUs) is minimized, subject to rate demands at the SUs, as well as the interference constraints imposed by primary users. Unlike the rate maximization problems, which are always feasible, this power minimization (PM) problem may be infeasible due to the rate constraints. Therefore, we provide a complete analysis of the PM problem by splitting the solution into two separate phases. In phase I, a novel method is developed to check the feasibility of the PM problem by considering an alternative problem, where one additional variable is introduced. This alternative problem is always feasible and one algorithm based on network duality and geometric programs is developed to solve it. In phase II, a novel algorithm is developed to solve the PM problem. This algorithm can be implemented in an online fashion. Furthermore, this algorithm is proved to converge to a Karush-Kuhn-Tucker point of the PM problem. Simulation results show that the proposed algorithms converge in only a few iterations and significantly outperform the existing single-band method in terms of both the feasibility probabilities and power savings.

Joint User Selection and Energy Minimization for Ultra-Dense Multi-channel C-RAN With Incomplete CSI

In this paper, we propose a transmit covariance optimization method to maximize the energy efficiency (EE) for the single-user distributed antenna system, where both the distributed antenna (DA) ports and the user are equipped with multiple antennas. Unlike previous related works, both the rate requirement and DA port selection are taken into consideration. Given this setup, we first propose an optimal transmit covariance optimization method to solve the EE optimization problem under fixed set of active DA ports and then the active DA port selection algorithm. For the transmit covariance optimization method, we split this problem into three subproblems, i.e., rate maximization problem, EE maximization problem without rate constraints, and power minimization problem. Then, a novel distance-based DA port selection method is proposed to determine the optimal set of active DA ports. Simulation results show that the performance of the proposed DA port selection is almost identical to the optimal exhaustive search method with significantly reduced computational complexity, and significantly outperforms the existing EE optimization methods.

Receiver Design for PAM-DMT in Indoor Optical Wireless Links

This paper investigates asymmetric two-way relay channels (TWRCs), where a couple of source nodes exchange data with different flow rates via a relay node. A novel mapping codebook-based physical network coding scheme is proposed for improving the performance of such channels. The proposed network coding scheme introduces a mapping codebook that contains several subcodebooks and adaptively selects a subcodebook from the mapping codebook in each data exchange based on the information of signal phase difference. Moreover, distributed transmission power control is also introduced to simplify codebook design and facilitate physical network coding. Simulation results show that it can significantly improve the BER performance as compared to analog network coding. It is also robust to the phase estimation error and the power control error, in particular, in a lower SNR region.