干擾 (interference) 對無線通訊而言是一個很大的瓶頸。由於在分散式的資源分配 (distributed resource allocation)，使用者實際在實體層 (Physical layer) 所經歷的干擾是突發 (bursty) 的，意即干擾不一定一直出現。若能妥善利用如此的特性以設計系統，則能得到顯著的效能增益。為了探討此潛在增益，我們在本篇論文考慮兩使用者多輸入單輸出突發性干擾通道 (two-user multiple-input single-output (MISO) bursty interference channel)，其中我們假設使用者之間的干擾在每個時槽 (time slot) 只有一定的機率出現。基於突發性狀態 (burstiness state) 的資訊，每個傳輸端會依照此資訊採用不同的波束 (beamforming) 以及傳輸速率來進行通訊。在此設定下，我們的目標為將平均系統效能最大化，並針對以下兩種情況考慮波束設計：a) 傳輸端有完整通道資訊 (perfect channel state information (CSI))， 以及 b) 傳輸端只有通道統計資訊 (channel distribution information (CDI))。以上兩種最佳化問題 (optimization problem) 皆為非凸(nonconvex)，並且困難。為了解決此問題，我們使用了ㄧ系列的凸近似 (convex approximation)，例如半正定放寬 (semidefinite relaxation (SDR)) 以及一階近似 (first-order approximation)。我們可進一步利用我們的連續凸近似演算法 (successive convex approximation (SCA) algorithm) 來改善我們的近似。除此之外，我們也提出了此演算法之收斂分析。透過模擬結果，我們驗證了此演算法的確能得到接近最佳解 (near-optimal solution)。此外，我們的結果也指出若能妥善運用干擾通道的突發性特性 (burstiness)，我們的確可以得到一個顯著的效能增益。

Interference, a main bottleneck in modern wireless communication, may not be always present in many practical situations. In fact, due to the bursty nature of traffic in wireless networks, the corresponding interference is also bursty in general. Such burstiness, if properly exploited, can provide significant gain in performance. To investigate this potential gain, a two-user multiple-input single- output (MISO) bursty interference channel is considered in this work. It is assumed that interference between users is only present with a certain probability. Based on the knowledge of burstiness status, each transmitter adopts a different beamforming strategy and a different rate for communication. Under this setting, we aim to maximize the average system utility and consider the optimal beamforming design for two cases: a) when perfect channel state information (CSI) is assumed, and b) when only channel distribution information (CDI) is assumed at transmitter end. Both optimization problems are nonconvex and difficult to solve. To handle such difficulty, we apply a series of convex approximation techniques such as semidefinite relaxation (SDR) and first-order approximation. Furthermore, we improve the approximation accuracy of our approximation through solving the approximated problem successively, and propose a successive convex approximation (SCA) algorithm. The convergence analysis for the proposed SCA algorithm is also provided. The near-optimal performance of our proposed SCA algorithm is demonstrated by simulations. Our results demonstrate that significant performance gain can be achieved by exploiting the bursty nature of wireless interference network.

1 Introduction-------------------------------------------1
2 System Model and Problem Statement---------------------5
3 Utility Maximization under Perfect CSI at Transmitters-9
4 Utility Maximization under Perfect CDI at Transmitters-20
5 Convergence Analysis-----------------------------------33
6 Simulation Results-------------------------------------41
7 Conclusion---------------------------------------------50
Appendix-------------------------------------------------51
Bibliography---------------------------------------------64

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