這篇論文檢驗了裝置到裝置傳輸系統（Device-to-device (D2D) communication system）實體層保密（physical layer security）的效能。在此系統中，裝置使用者會要求不同層級的安全性（secrecy guarantees）且備有感測周圍竊聽者的能力。使用者、竊聽者以及基地台以三層獨立卜瓦松點過程（Poisson point processes）建模。裝置傳輸者暴露在竊聽者偷聽保密訊息的威脅下。我們推得D2D傳輸機率的閉合 (close-form) 形式，以及當D2D傳輸者能確知在偵測範圍內的竊聽者數目下條件洩密機率的緊密上界。該分析亦能沿用到偵測範圍無限大（等價於只知道使用者密度的情況），和偵測範圍分成多層（能夠提供更精確的竊聽者位置資訊）。利用求得的解析結果 (analytic result)，我們建立一個最佳化問題，為K層安全層級的D2D傳輸者設定最佳發射功率 (power) 和傳輸率 (rate) ，最大化所有安全層等效流通量總和 (effective sum throughput)，附帶預先設定的保密性 (secrecy)、發射功率和傳輸率的限制。我們的結果顯示等效保密工作量（effective secrecy throughput）能在偵測竊
聽者並得知其數目的狀況下大幅增加。

This work examines the effectiveness of physical layer secrecy in (in-band) device-to-device (D2D) communication systems. Here, D2D users may require different levels of secrecy guarantees and are assumed to be equipped with the cognitive capability of sensing the presence of eavesdroppers in its vicinity. Users, eavesdroppers and base stations are modeled as three independent homogeneous Poisson point processes. D2D transmitters are under threat from eavesdroppers overhearing confidential messages. We derive a closed-form expression for the connection outage probability and a tight upper bound on the secrecy outage probability when each D2D transmitter can sense the exact number of eavesdroppers in its sensing area. This analysis can also be applied to cases where the sensing area is infinitely large (which is equivalent to the case where only the user density is known) and where sensing areas can be divided into multiple layers (which provides more accurate location information to the transmitter). Using the derived analytic results, we formulate an optimization problem that aims to jointly and optimally allocate powers and rates for D2D transmitters with K different security levels so as to maximize the effective sum throughput under some predesignated secrecy, power and rate constraints. Our results show that the effective secrecy throughput of the system can be significantly increased with the aid of the cognitive information of the number of the eavesdroppers within the vicinity of a D2D transmitter.

Abstract i
Contents ii
1 Introduction 1
2 System Model 5
3 Secrecy Outage Analysis for Cognitive D2D Communication 9
3.1 Scenario I: Without Information of Nearby Eavesdroppers . . . . . . . . . . 10
3.2 Scenario II: Knowing n Eavesdroppers inside the Cognitive Area . . . . . . . 11
3.2.1 Proof of Upper Bound for Secrecy Outage Probability with Knowing
Number of Eavesdroppers . . . . . . . . . . . . . . . . . . . . . . . . 12
4 Rate and Power Allocation Policies with/without Cognitive Capability 14
4.1 Scenario I: Naive Rate and Power Allocation . . . . . . . . . . . . . . . . . . 14
4.2 Scenario II: Eavesdropper-Number-Based Rate Allocation (Fixed Power) . . 19
5 Extension to the Case with Multi-Layer Cognitive Information 23
5.1 Conditional Secrecy Outage Probability with Knowing Eavesdropper Numbers
in Detection Zones . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 23
5.1.1 Proof of Upper Bound for Secrecy Outage Probability with Knowing
Eavesdropper Numbers in Detection Zones . . . . . . . . . . . . . . . 24
5.2 Detection-Zone-Based Rate Allocation
(Fixed Power) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 26
6 Numerical Simulations 28
7 Conclusion 35
A Proof in Chapter 4 36
A.1 Proof of theorem . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 36
A.1.1 Quasi-concavity in ν_k . . . . . . . . . . . . . . . . . . . . . . . . . . . 36
A.1.2 Quasi-concavity in R_E,k . . . . . . . . . . . . . . . . . . . . . . . . . 37
A.1.3 Quasi-concavity in R_D,k . . . . . . . . . . . . . . . . . . . . . . . . . 37

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