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Copyright of Journal on Communication / Tongxin Xuebao is the property of Journal on Communications Editorial Office and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Pilot contamination due to pilot reuse seriously mitigates the performance of the cell-free massive multiple-input multiple-output (MIMO) systems. In this paper, we propose a joint pilot assignment scheme that employs user clustering and graph coloring (UC-GC) to reduce pilot contamination. The proposed method consists of two steps: firstly, we utilize AP selection to classify all users; secondly, we assign pilots to users with more severe pilot contamination using the graph coloring algorithm and then assign pilots to the remaining users. The numerical simulation results show that the proposed scheme outperforms existing pilot assignment schemes and significantly improves throughout with low complexity. [ABSTRACT FROM AUTHOR]

Pilot contamination due to pilot reuse seriously mitigates the performance of the cell-free massive multiple-input multiple-output (MIMO) systems. In this paper, we propose a joint pilot assignment scheme that employs user clustering and graph coloring (UC-GC) to reduce pilot contamination. The proposed method consists of two steps: firstly, we utilize AP selection to classify all users; secondly, we assign pilots to users with more severe pilot contamination using the graph coloring algorithm and then assign pilots to the remaining users. The numerical simulation results show that the proposed scheme outperforms existing pilot assignment schemes and significantly improves throughout with low complexity.

Copyright of Telecommunications Science is the property of Beijing Xintong Media Co., Ltd. and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Cell-Free massive MIMO (mMIMO) offers promising features such as higher spectral efficiency, higher energy efficiency and superior spatial diversity, which makes it suitable to be adopted in beyond 5G (B5G) networks. However, the original form of Cell-Free massive MIMO requires each AP to be connected to CPU via front haul (front-haul constraints) resulting in huge economic costs and network synchronization issues. Radio Stripe architecture of cell-free mMIMO is one such architecture of cell-free mMIMO which is suitable for practical deployment. In this paper, we propose DNN Based Parallel Decoding in Radio Stripe (DNNBPDRS) to decode the symbols of User Equipments (UEs) in the uplink in a parallel fashion to reduce computational complexity by reducing delay in processing. Moreover, to solve the issue of Access Point (AP) selection in radio stripe networks, we propose a Channel link-based AP selection (CLBAPS) algorithm to choose the best APs in terms of channel link quality. The proposed DNNBPDRS framework not only improves Symbol Error Rate (SER) performance when compared to counterparts but is also proved to be comparatively far lesser computational complex. Moreover, the numerical result indicates the proposed AP selection algorithm CLBAPS performs better than random selection of AP in radio stripe networks. [ABSTRACT FROM AUTHOR]

How to meet the demand for increasing number of users, higher data rates, and stringent quality-of-service (QoS) in the beyond fifth-generation (B5G) networks? Cell-free massive multiple-input multiple-output (MIMO) is considered as a promising solution, in which many wireless access points cooperate to jointly serve the users by exploiting coherent signal processing. However, there are still many unsolved practical issues in cell-free massive MIMO systems, whereof scalable massive access implementation is one of the most vital. In this paper, we propose a new framework for structured massive access in cell-free massive MIMO systems, which comprises one initial access algorithm, a partial large-scale fading decoding (P-LSFD) strategy, two pilot assignment schemes, and one fractional power control policy. New closed-form spectral efficiency (SE) expressions with maximum ratio (MR) combining are derived. The simulation results show that our proposed framework provides high SE when using local partial minimum mean-square error (LP-MMSE) and MR combining. Specifically, the proposed initial access algorithm and pilot assignment schemes outperform their corresponding benchmarks, P-LSFD achieves scalability with a negligible performance loss compared to the conventional optimal large-scale fading decoding (LSFD), and scalable fractional power control provides a controllable trade-off between user fairness and the average SE. [ABSTRACT FROM AUTHOR]