Abstract-We consider a multi-way massive multiple-input multiple-output relay network with zero-forcing processing at the relay. By taking into account the time-division duplex protocol with channel estimation, we derive an analytical approximation of the spectral efficiency. This approximation is very tight and simple which enables us to analyze the system performance, as well as, to compare the spectral efficiency with zero-forcing and maximum-ratio processing. Our results show that by using a very large number of relay antennas and with zero-forcing technique, we can simultaneously serve many active users in the same timefrequency resource, each with high spectral efficiency. I. INTRODUCTIONMulti-way relay networks are relevant for many applications, such as data transfer in multimedia teleconference and data exchange between sensor nodes and data fusion centers in wireless communications [1]. Due to the multiplexing gain, the spectral efficiency of multi-way relay networks is much larger than that of two-way or one-way relay networks. Therefore, during the past years, multi-way relay networks have attracted considerable research interest [2]. On a parallel avenue, massive multiple-input multiple-output (MIMO) has also attracted a significant amount of research interest from both academia and industry [3]. In massive MIMO, hundreds of antennas are deployed at the base station to serve simultaneously tens of users. With simple linear processing techniques, such as maximum-ratio (MR) or zero-forcing (ZF) processing, massive MIMO can offer huge spectral and energy efficiency [4]. Thus, massive MIMO combined with multi-way relaying technique is a strong candidate for the next-generation wireless communication systems.Recently, there have been some works in multi-way massive MIMO relay systems [5], [6]. These systems can offer all benefits of both massive MIMO and multi-way relaying technologies, and hence, are expected to offer very high spectral efficiency. In particular, in [5], the authors show that by using very large antenna arrays at the relay together with ZF processing, the system performance can improve significantly. Furthermore, [6] shows that the transmit power of each user and/or the relay can be made inversely proportional to the number of relay antennas, while maintaining a required quality of service. However, these works assume perfect channel state information (CSI) at the relay and users. In practice, especially in massive MIMO systems, the impact of channel estimation should be taken into consideration. In [7], the authors analyze

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Abstract-This paper considers a multi-way massive multipleinput multiple-output relaying system, where single-antenna users exchange their information-bearing signals with the help of one relay station equipped with unconventionally many antennas. The relay first estimates the channels to all users through the pilot signals transmitted from them. Then, the relay uses maximumratio processing (i.e. maximum-ratio combining in the multipleaccess phase and maximum-ratio transmission in the broadcast phase) to process the signals. A rigorous closed-form expression for the spectral efficiency is derived. The effects of the channel estimation error, the channel estimation overhead, the length of the training duration, and the randomness of the user locations are analyzed. We show that by deploying massive antenna arrays at the relay and simple maximum-ratio processing, we can serve many users in the same time-frequency resource, while maintaining a given quality-of-service for each user.Index Terms-Channel state information, massive MIMO, multi-way relay networks.

Abstract-This paper considers a multi-way massive multiple-input multiple-output (MIMO) relaying system. The bearing-information is exchanged among multiple users with the help of a multiple-antenna relay (the base station). The maximum-ratio (MR) processing is applied at the relay under the assumption of perfect channel state information. The spectral efficiency and the asymptotic results for the signal-to-interference-plus-noise ratio (when the number of relay antennas becomes large) are derived. By using a massive number of antennas, the transmit power at both user side and/or relay can be made inversely proportional to the number of relay antennas without degradation in the system performance.Index Terms-Massive MIMO, maximum-ratio processing, multi-user MIMO, multi-way relay networks, zero-forcing processing.

This paper considers a decode-and-forward (DF) multi-way massive multiple-input multiple-output (MIMO) relay system where many users exchange their data with the aid of a relay station equipped with a massive antenna array. We propose a new transmission protocol which leverages successive cancelation decoding and zero-forcing (ZF) at the users. By using properties of massive MIMO, a tight analytical approximation of the spectral efficiency is derived. We show that our proposed scheme uses only half of the time-slots required in the conventional scheme (in which the number of time-slots is equal to the number of users [1]), to exchange data across different users. As a result, the sum spectral efficiency of our proposed scheme is nearly double the one of the conventional scheme, thereby boosting the performance of multi-way massive MIMO to unprecedented levels. To improve the network energy efficiency, we also propose a power allocation scheme which maximizes the energy efficiency under a given peak power constraint at each user and the relay. Index Terms-Decode-and-forward, massive MIMO, multiway relay system, power allocation, spectral and energy efficiency.

We consider a multi-way decode-and-forward (DF) relaying network with very large antenna arrays at the relay station. In this system, each user and the relay operate in halfduplex and time-division duplexing (TDD) modes. To exchange information among all users, we propose a new transmission protocol which combines massive multiple-input multiple-output (MIMO) technology with linear processing, self-interference cancelation, and successive cancelation decoding. Our proposed transmission protocol reduces the number of time-slots for data exchange among users by approximately 2 times, compared to the conventional data transmission protocol. For this new topology, we derive a very tight approximation of the spectral efficiency in closed-form assuming perfect channel state information (CSI). Then, CSI acquisition method at the relay and the users is provided and analysed. We show via numerical simulations, the performance gap between imperfect and perfect CSI cases is small. The closed-form expression of the spectral efficiency enables us to design two power allocation schemes. In the first power allocation scheme, we choose the transmit powers at the users and the relay to maximize the sum spectral efficiency, subject to a given quality-of-service requirement for each user. In the second power allocation scheme, the objective is the energy efficiency taking into account the hardware power consumption. Both power allocation schemes can be efficiently executed by iteratively solving a sequence of convex problems. Numerical results verify the effectiveness of the proposed transmission protocol and the power allocation schemes compared to the stateof-the-art.Index Terms-Amplify-and-forward, decode-and-forward, maximum-ratio processing, multi-way relay massive MIMO, power allocation, successive cancelation decoding.• We propose a new transmission protocol which relies on massive MIMO technology and successive cance-