適用於無線協作式網路中增強型行動寬頻網路之預編碼器最佳化設計

Precoder Optimization for Supporting Enhanced Mobile Broadband in Wireless Cooperative Networks

林哲毅(Jhe-Yi Lin)

指導教授 ： 曹恆偉

共同指導教授 ： 蘇炫榮(Hsuan-Jung Su)

國立臺灣大學/電機資訊學院/電子工程學研究所/博士(2019年)

https://doi.org/10.6342/NTU201900306

摘要

針對解決在無線協作式網路中支援增強型行動寬頻網路所遇到的挑戰，本論文提出創新的演算法。其中，我們特別針對三個主要的研究挑戰提出我們的演算法，這三個挑戰分別是網路稠密化(network densification)、自干擾消除(self-interference cancellation)和維持營運商利潤 (maintain profitability)。

網路稠密化提升了網路的容量，但也造成干擾限制效能(interference-limited performance)的問題。因此，我們考慮使用廣線性預編碼器(widely-linear precoder)來解決無線協作式網路中干擾限制效能(interference-limited performance)的問題。其中，對於如何在干擾限制效能的網路中最大化速率，improper Gaussian signaling (IGS)已經被證實可以達到比proper Gaussian signaling (PGS)更好的效能。因此，在論文的第一部份，我們研究在多重輸入輸出的干擾廣播通道中使用IGS的權重速率總和最大化問題。在干擾廣播通道中，權重速率總和最大化問題是一個非凸(nonconvex)且NP-hard的問題。因此，為了有效率的計算出最佳解，我們提出了一個共變異數矩陣和虛擬共變異數矩陣分別最佳化演算法。在共變異數矩陣最佳化的部分，我們使用權重最小均方誤差(WMMSE)演算法；在虛擬共變異數矩陣最佳化的部分，我們提出一個可以保證收斂到靜態點的交替式最佳化(alternating optimization, AO)演算法。除此之外，我們提出的AO演算法也可以保證使用IGS的權重速率總合一定比使用PGS的權重速率總合還高。

最近，在協作式傳輸中使用全雙工中繼站受到重視，因為它可以延伸服務覆蓋和提高網路容量。然而，全雙工中繼站的自干擾會嚴重降低端到端速率。因此，如何消除自干擾是全雙工中繼站能否實用化的關鍵問題。另一方面，考慮到中繼站常常被不屬在偏遠區域，我們假設中繼站是透過無線電波能源採集技術來供電。為了有效的利用全雙工技術提升頻譜效率的能力，在本論文中我們使用功率分配(power-splitting, PS)架構來實現無線電波能源採集技術。在PS架構中，一個關鍵的問題是如何設計PS係數，使得中繼站能更有效率的利用採集到的能源來提升端到端速率。為了同時解決自干擾消除和PS係數設計問題，我們提出使用IGS來降低自干擾對於效能的影響並提升端到端速率。其中，為了在全雙工中繼站中使用IGS，我們首先推導出全域最佳的虛擬共變異數和PS係數的關係式。接著，根據這個關係式，我們提出了一個能保證收斂到靜態點的AO演算法。最後，透過模擬結果，我們可以驗證我們提出的AO演算法具有較高的端到端速率。

能源使用效率(energy efficiency, EE)是設計移動網路常見的效能指標，因為網路營運商除了要滿足用戶的需求而且必須降低營運成本(主要是電費)以維持長期競爭力。然而，對於以使用者微中心的服務，使用者體驗品質(quality of experience, QoE)是一個更合適的效能指標。因此，在論文的第三部分，我們提出了一個新的效能指標，也就是quality-energy efficiency (QEE)。QEE結合了QoE和EE，能同時考慮使用者體驗品質和能源使用效率。另一方面，針對如何運用QEE來設計以使用者為中心的節能移動網路，我們提出了一個設計框架。在我們的設計框架中，我們利用大型網路中傳輸的稀疏特性來簡化問題，並利用區塊座標下降法 (block-coordinate descent, BCD)來設計一個保證收斂的演算法。最後，透過模擬結果，我們可以驗證我們提出的演算法可以達到接近全域最佳的效能，並且在各種網路參數下都可以有優異的表現。

關鍵字

無線協作式網路 ； 增強型行動寬頻網路 ； 預編碼 ； improper Gaussian signaling權重速率總和最大化 ； 全雙工中繼站 ； 同時訊息及能量傳輸 ； 能源使用效率 ； 使用者體驗品質.

並列摘要

The focus of this thesis is to develop algorithmic approaches to resolve challenges of supporting eMBB in cooperative networks. Specifically, we resolve the challenges of network densification, self-interference cancellation, and maintaining profitability.

For the challenge of network densification, we consider employing widely linear precoding to mitigate the interference-limited performance issue in wireless cooperative networks. For rate optimization in interference limited network, improper Gaussian signaling has shown its capability to outperform the conventional proper Gaussian signaling. In the first part of this thesis, we study a weighted sum-rate maximization problem with improper Gaussian signaling for the multiple-input multiple-output interference broadcast channel (MIMO-IBC). To solve this nonconvex and NP-hard problem, we propose an effective separate covariance and pseudo-covariance matrices optimization algorithm. In the covariance optimization, a weighted minimum mean square error (WMMSE) algorithm is adopted, and, in the pseudo-covariance optimization, an alternating optimization (AO) algorithm is proposed, which guarantees convergence to a stationary solution and ensures a sum-rate improvement over proper Gaussian signaling. An alternating direction method of multipliers (ADMM)-based multi-agent distributed algorithm is proposed to solve an AO subproblem with the globally optimal solution in a parallel and scalable fashion. The proposed scheme exhibits favorable convergence, optimality, and complexity properties for future large-scale networks. Simulation results demonstrate the superior sum-rate performance of the proposed algorithm as compared to existing schemes with proper as well as improper Gaussian signaling under various network configurations.

Recently, cooperative transmission with full-duplex (FD) relays has gained lots of attention because it can extend service coverage and improve network capacity. However, the self-interference of the FD relay greatly degrade the end-to-end system throughput. As a result, we propose using improper Gaussian signaling (IGS) in joint source and relay transmission to achieve a better LI resistance and, as a result, a better end-to-end system throughput in energy harvesting (EH) enabled FD relaying systems. An alternating optimization (AO) algorithm is proposed to solve the challenging design problem of finding the optimal transmission with IGS at both the source and relay, as well as the optimal power-splitting (PS) factor at the EH-enabled relay. The relationship between the PS factor and the optimal pseudo-variances is derived in closed form. Numerical results demonstrate the superior throughput performance yielded by IGS at the same LI level, and suggest the possibility of employing IGS as a replacement of a sophisticated LI canceller in practical FD relaying systems.

Since mobile network operators not only need to satisfy user needs but also have to reduce operating cost (mainly electricity cost) to maintain long-term profitability under strict market competition, energy efficiency (EE), defined as capacity per energy cost, becomes a popular metric for designing mobile networks. For user-centric services, however, the metric of quality of experience (QoE) is more suitable than the metric of capacity or data rate. Therefore, in the third part of this thesis, we consider a novel network design metric quality-energy efficiency (QEE), defined as the quality of experience achieved per energy consumed. By using QEE as the performance objective, we propose a framework to design user-centric green cloud-based radio access network (C-RAN). In particular, the issues of fairness and fronthaul power consumption in C-RAN are taken into account. An efficient approach to solving the non-convex max-min optimization problem for the design of user-centric green C-RAN is proposed. Simulation results validate the near-optimal performance of the proposed algorithm and demonstrate the value of the proposed QEE metric for the design of energy-efficient user-centric C-RAN.

並列關鍵字

wireless cooperative network ； eMBB ； precoding ； improper Gaussian signaling ； sum-rate maximization ； full-duplex relay ； SWIPT ； energy efficiency ； quality of experience

參考文獻

[1] https: //ppt.cc/ fM5eix.

[2] T.-H. Chang, M. Hong, and X. Wang, "Multi-agent distributed optimization via inexact consensus ADMM," IEEE Trans. Signal Process., vol. 63, no. 2, pp. 482-497, Jan. 2015.

[3] Cisco VNI Forecast, "Cisco visual networking index: Global mobile datatraffic forecast update 2014-2019," Cisco Public Information, Feb. 2015.

[4] J.-Y. Lin, R. Y. Chang, C.-H. Lee, H.-W. Tsao, and H.-J. Su, "Multiagent distributed beamforming with improper Gaussian signaling for MIMO interference broadcast channels," IEEE Trans. Wireless Commun., vol. 18, no. 1, pp. 136-151, Jan. 2019.

[5] J.-Y. Lin, R. Y. Chang, C.-H. Lee, and H.-W. Tsao, "Distributed beamforming with improper Gaussian signaling for MIMO interference broadcast channels," in Proc. IEEE Global Communications Conference (GLOBECOM), Dec. 2017.