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The emerging fifth generation（5G） wireless communication system raises new requirements on spectral efficiency and energy efficiency. A massive multiple-input multiple-output（MIMO） system, equipped with tens or even hundreds of antennas, is capable of providing significant improvements to spectral efficiency,energy efficiency, and robustness of the system. For the design, performance evaluation, and optimization of massive MIMO wireless communication systems, realistic channel models are indispensable. This article provides an overview of the latest developments in massive MIMO channel measurements and models. Also, we compare channel characteristics of four latest massive MIMO channel models, such as receiver spatial correlation functions and channel capacities. In addition, future challenges and research directions for massive MIMO channel measurements and modeling are identified.

With the rapid development of information technology, massive MIMO is becoming attractive for the fifth generation（5G） communication because of its outstanding performance in both spectral efficiency（SE）and energy efficiency（EE）. Recently, many algorithms have been proposed to improve the EE while achieving high SE in massive MIMO systems. In previous work, the power amplifier（PA） efficiency is always considered as a constant. However, the PA efficiency changes with the output power in reality. In the practical situation,the simplification which treats the PA efficiency as a constant will not get the EE optimization based on our analysis. In this paper, we propose a more general EE model of massive MIMO systems considering PA efficiency as a variable, and investigate a power allocation algorithm based on zero-forcing（ZF） precoding so that we can guarantee the SE and EE at the same time. Simulation results show the trade-off between EE and SE, demonstrate the distinction with previous work, and imply that relatively higher transmit power will be more energy efficient.

A sectorization method using the uniform circular array（UCA） is proposed to improve the net spectral efficiency（SE） of the multicell massive MIMO system, which is an important index for evaluating the performance of a communication system. We derive the ergodic achievable uplink net SE per cell of a general sectorized system and obtain its deterministic approximation based on the large random matrix theory.Different weight matrices are considered for the sectorized system and the one with the best performance is utilized for further analysis. The consistency of the deterministic approximation with the result of Monte-Carlo simulation is proved at the same time. At last, numerical results indicate that the net SE per cell can be greatly improved compared to the conventional multicell massive MIMO system, which validates the effectiveness of the sectorization method. Moreover, comparisons with other pilot reuse methods are also made in this paper.

Large-scale MIMO （multiple-input multiple-output） systems with numerous low-power antennas can provide better performance in terms of spectrum efficiency, power saving and link reliability than conventional MIMO. For large-scale MIMO, there are several technical issues that need to be practically addressed （e.g., pilot pattern design and low-power transmission design） and theoretically addressed （e.g., capacity bound, channel estimation, and power allocation strategies）. In this paper, we analyze the sum rate upper bound of large-scale MIMO, investigate its key technologies including channel estimation, downlink precoding, and uplink detection. We also present some perspectives concerning new channel modeling approaches, advanced user scheduling algorithms, etc.

Because modern communication networks are expected to deliver increasingly high data rates at a decreas- ing cost per bit, the spectral efficiency of communication systems must be further improved to facilitate emerging ubiquitous services. Furthermore, because future communication networks will comprise a large number of network elements with varying functionalities/capabilities, the property of high heterogeneity will need to be observed in such netwarks.

With the development of communication technology, the precious frequency spectrum is becoming more and more crowded. Exploiting the particular filter with zero group delay, ultra narrow band （UNB） modulation is intended for acquiring the high frequency efficiency. Unfortunately, this UNB filter is confronted with great challenges from the classical communication theories. The validation on its realization is also difficult. This paper proposes a novel UNB modulation, namely random pulse position keying （RPPK）. It is demonstrated from analysis that there is no inessential discrete spectral line in modulated signal＇s power density spectrum （PDS）, and the UNB filter has been successfully avoided. Consequently, RPPK is rather explicit in theory and simple in implementation. As is shown by the simulation, the frequency utilization of RPPK can even reach 100 bits/s/Hz. Its optimum receiving performance is slightly inferior to BPSK, yet is much superior to that of other UNB modulations such as VMSK/2. Moreover, multi-access and confidentiality are additional benefits to UNB users.

In this study we propose a hybrid spectrum sharing scheme based on power control by combining Overlay with Underlay schemes, to improve radio spectrum efficiency. In the scheme, the secondary users dynamically switch their operational states between Overlay and Underlay according to the spectrum occupancy. Thus the dynamics of the primary network is first modeled with a discrete-state Markov process to find the time fraction of secondary users in the Overlay state and that in the Underlay state, which leads to the capacity model of the hybrid spectrum sharing system. Under the criterion of maximizing capacity, the power allocation of the cognitive network is researched and the optimum power allocation for secondary users is deduced. As a result, the maximum achievable capacity of the cognitive network is obtained. Simulations are given to prove the analysis further. Theoretical and simulated results indicate that hybrid spectrum sharing based on power control provides a higher capacity than single Overlay and Underlay systems for the cognitive network, i.e., hybrid spectrum sharing can further improve radio spectrum efficiency.