无线通信物理层安全技术：分类与应用综述

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"这篇PDF文章是对无线通信物理层安全（Physical Layer Security, PLS）的综合概述。PLS是一种新兴的概念，它作为加密方法的强大补充，甚至可能替代传统加密技术，因为加密技术在未来的无线系统中面临许多挑战和实际问题。PLS的核心是利用无线信道的特性，如噪声、衰落、干扰、色散和多径等，来确保合法接收者能成功解码数据，同时阻止窃听者进行同样的操作。设计PLS的主要目标是通过采用精心设计的传输策略来增大合法接收者与窃听者之间的性能差异。" 文章详细介绍了PLS的分类和应用，这包括了不同类型的物理层安全技术，旨在提高机密性。以下是一些关键知识点： 1. **物理层安全的基本原理**：PLS的核心在于利用无线信道的随机性和不可预测性来增强通信的安全性。这与传统的基于加密的方法不同，后者依赖于数学上的复杂性来保护数据。 2. **信道特性**：信道的噪声、衰落、干扰和色散等特性在PLS中被视作资源，而非干扰因素。这些特性可以被巧妙地利用来创建只有合法接收者才能解码的信息流。 3. **传输策略设计**：设计针对特定信道环境的传输策略是PLS的关键。这些策略可能包括空间分集、频率分集、时间分集或多模式传输，以增加窃听者解码的难度。 4. **分类**：PLS技术可以分为多个类别，如无线信道的随机性利用、信息论安全分析、能量检测、干扰管理以及多种安全编码方案。每种分类都有其独特的应用场景和优势。 5. **应用**：PLS在无线通信领域的应用广泛，包括但不限于移动通信、物联网(IoT)、认知无线电网络、卫星通信和无线传感器网络等。在这些领域，PLS可以提供额外的安全保障，特别是在资源有限和加密不适用的情况下。 6. **挑战与未来方向**：虽然PLS提供了新的安全途径，但它也面临着一些挑战，比如如何在动态变化的信道环境中保持安全性，以及如何在大规模网络中实现高效的PLS策略。未来的研究将集中在解决这些问题，并探索新的理论和技术以增强PLS的性能。这篇综述文章深入探讨了物理层安全的各种技术和应用，对于理解无线通信中的安全问题以及如何利用物理层特性来增强安全性具有重要意义。

1553-877X (c) 2018 IEEE. Personal use is permitted, but republication/redistribution requires IEEE permission. See http://www.ieee.org/publications_standards/publications/rights/index.html for more information.

This article has been accepted for publication in a future issue of this journal, but has not been fully edited. Content may change prior to final publication. Citation information: DOI 10.1109/COMST.2018.2878035, IEEE

Communications Surveys & Tutorials

LDPC,

Polar,

etc.

codes.

e.g., adaptive

modulation,

adaptive power

allocation,

optimized

waveform, ARQ,

pre-equalization.

e.g., OFDM

Subcarrier-

based power

allocation,

pre-coding.

Note 1: There are hybrid security techniques, which use two or more of the above mentioned

techniques simultaneously to ensure security in different scenarios.

Note 2: Most of the physical layer security technique proposed in the literature can be classified and fit

under one of the above-mentioned categories.

Symbol

level

Bit-

level

Space-

time,

Reed-

Solomon

, etc.

codes

The Big Picture of Physical Layer Security Techniques against Wireless Passive Eavesdropping: P2

Channel-based

adaptation. [II]

SINR-based (Key-less) approach

Channel quantization based secret

key extraction to randomize the data

on a bit or symbol level basis. [IV]

Complexity-based (Key) approach

Time

Injection of artificial

(noise/jamming/

interfering) signals

to the data. [III]

Frequency

Space

Enabling Techniques

Time

Enabling Techniques

Frequency

Space

Time

Frequency

Channel

coding. [I]

Space

Beamforming,

pre-coding

(PMI), power

allocation in

MIMO, MISO

SIMO, relays,

COMP, ASM,

SM, DM, DAS.

AN with

ARQ, AN in

multi-path

e.g., OFDM

with AN by

exploiting

CP feature.

e.g., AN injection by

exploiting the degree of

freedom exists in MIMO,

MISO, relays, COMP, etc.

e.g.,

exploiting

channel

variation

caused by

Doppler

and multi-

path over

time.

e.g., exploiting

channel variation

over sub-carriers

in OFDM systems.

e.g.,

exploiting

channel

variation

over

antennas

or relays.

Fig. 4. The big picture of the classiﬁcation structure (including examples in the three main signal domains: time, frequency, and space) of physical layer

security techniques against wireless passive eavesdropping: Part two (P2).

Communications Surveys & Tutorials

assessed the behavior of some LDPC code design techniques

over the AWGN wiretap channel, in terms of security gap.

In [43], the authors studied the application of a special type

of LDPC codes based on serially concatenated low-density

generator matrix to the Gaussian wiretap channel. In [44],

the equivocation rate of Eve’s channel is exploited as an

optimization criteria for designing an algorithm in the ﬁnite

codeword length regime. By using this algorithm, irregular

LDPC codes with smaller codeword lengths are constructed

that can approach the ultimate performance limits.

A brief summary of some of the key contributions related

to secure LDPC codes is provided in Table II.

Recently, polar codes, which are known as capacity achiev-

ing codes, are proposed to be used as secrecy capacity

achieving codes too. In [45], authors used polar codes to

construct a coding scheme that achieves the secrecy capacity

for a wide range of wiretap channels. Their scheme works

for any instantiation of the wiretap channel model, as long as

both main and wire-tap channels are symmetric and binary-

input, and wire-tap channel is degraded with respect to the

main channel. Moreover, they clariﬁed how to modify their

construction in order to provide strong security, in the sense

deﬁned by Maurer. In [46], it was shown that polar codes

can achieve nonzero perfect secrecy rates for the binary-

input degraded wiretap channel with low encoding-decoding

complexity. Also, in the special case of having symmetric

channels for both Bob and Eve, this coding technique achieves

the secrecy capacity. This approach was also extended to the

multiple-access channel with a degraded eavesdropper where

a nontrivial achievable secrecy region is established. In [47], a

new multi-block polar coding scheme is introduced on top of

[45] to resolve the difﬁculty in providing both strong security

and reliability using polar codes, which occurs due to the

existence of a small number of bit-channels that are both

unreliable and unsecure.

In [48], authors proposed a concatenated coding scheme

based on polar codes and LDPC codes for the AWGN wiretap

channel. They also presented a transmission scheme using

rate compatible Polar-LDPC codes to adapt for different dy-

namic environments. In [49], a feedback-based secrecy coding

scheme using polar code over wiretap channels was proposed,

where authors’ results show that the proposed scheme using

polar code can transmit conﬁdential messages reliably and

securely. In [50], authors proposed an alternative approach

to the traditional way of generating secret keys, based on

polar codes that jointly deals with reliability and secrecy. In

[51], a low-complexity and secrecy capacity achieving polar

coding scheme was developed for the discrete memoryless

wiretap channel. The scheme extends previous work by us-

ing a nearly optimal amount of uniform randomness in the

stochastic encoder, and avoiding assumptions regarding the

symmetry or degraded nature of the channels. In [52], polar

codes are developed to relax the symmetric and degraded

constraints. In addition, the coding scheme is also extended to

the interference channel with conﬁdential message (IC-CM),

broadcast channel with conﬁdential message (BC-CM), and

to the multiple access wiretap channel (MA-WC). Besides,

a secrecy capacity achieving coding scheme is introduced

in [53] for general wiretap channel based on polar codes

(not necessarily symmetric or degraded). In [54], the authors

proposed an interesting security technique for the wiretap

channel based on polar codes and artiﬁcial noise (AN). In

this technique, the channel quality advantage of Bob over over

that of Eve is not assumed. In the ﬁrst step, upper and lower

bounds on the symmetric capacity of the polarized bit-channels

are derived that depends on the SNR of each use of physical

channel. Based on these bounds they prove that there is an

existence of bit channels that are hostile to signal reception of

the wiretap channel but beneﬁcial to main channels. Moreover,

they also introduce a method to achieve these bit channels

based on injecting AN and also prove the security of proposed

AN method theoretically. Furthermore, they also introduce two

power allocation schemes for AN.

A short summary of some of the main contributions related

to secure polar codes is made in Table III.

Besides designing security schemes based on LDPC and

polar codes, there are other secrecy schemes based on lattice

codes such as the works reported in [55], [56] and [57]. In

addition, the application of the practical convolutional and

turbo codes to Gaussian wiretap channel using randomized

encoding approach and based on using security gap metric

has recently been studied in [58].

Lesson 1: Most of the security codes surveyed in the

aforementioned studies are usually designed based on the

criterion of weak or strong secrecy notion which generally

assumes inﬁnite block length, making it less practical for

multimedia communication services (such as voice, video,

etc.) where the block length is ﬁnite due to having constraints

on the delay and throughput of these type of services that also

do not usually require perfectly zero block error probability.

Particularity, the research community should pay more atten-

tion to the fact that we need to design practical security codes

for the cases where the block length is ﬁnite

(does not go to

inﬁnity [63]), and secrecy rate does not necessary require to be

exactly equal to the main channel capacity where there is zero

information leakage to Eve. This is due to the fact that Eve

cannot practically beneﬁt from a service that does not meet or

comply with its minimal quality requirements. Moreover, the

design of practical security codes that not only can achieve the

secrecy capacity limit of ﬁnite block length, but also comply

with the practical constrains including delay, throughput and

complexity of some of the emerging communication services

in 5G and beyond scenarios such as URRLC and mMTC

remains a challenging task to achieve. Besides, to the best of

authors’ knowledge, designing generic secrecy codes without

considering any information knowledge on the channel of the

eavesdropper (which is a very practical scenario) is also not

yet clear or known thus far in the literature. Therefore, novel

coding techniques are indeed needed to address the above

challenges.

Note that there are a few primarily recent theoretical results related to the

fundamental limits of secrecy coding for ﬁnite block length as can be found

in [59]–[62].

Communications Surveys & Tutorials

TABLE II

CHANNEL CODING FOR PHYSICAL LAYER SECURITY (LDPC CODES)

Authors Year Contributions and Concepts

A. Thangaraj et al.

[38]

2007 Nested sparse graph-based LDPC codes are used to achieve the secrecy capacity when Bob’s channel is

noiseless, whereas Eve’s channel is binary erasure channel (BEC).

R. Liu et al. [39] 2007 A secure nested LDPC code structure with a new achievable secrecy rates is presented whose performance

is better than the previously reported result by [38] when the main channel is noiseless and the eavesdropper

channel is general binary-input symmetric-output memoryless channel.

C.-H. Hsu et al. [40] 2008 It is proven that capacity-achieving codes of any memoryless binary-input output-symmetric channel can

be constructed under ML decoding by puncturing some original LDPC codes with small enough rate

considering same scenario as [38], [39].

D. Klinc et al. [41] 2011 A practical coding scheme based on LDPC for Gaussian wiretap channel is presented which is encodable

in linear time, applicable at ﬁnite block lengths, and can be combined with existing cryptographic schemes

to provide improved data security.

N. Maturo et al. [42] 2013 The behavior of some LDPC code design techniques is addressed over the AWGN wiretap channel in terms

of security gap.

Nooraiepour et al.

[43]

2018 The application of a special type of LDPC codes based on serially concatenated low-density generator

matrix to the Gaussian wiretap channel is investigated.

TABLE III

CHANNEL CODING FOR PHYSICAL LAYER SECURITY (POLAR CODES)

Authors Year Contributions and Concepts

H. Mahdavifar et al.

[45]

2011 Polar codes are used to construct a coding scheme that achieves the secrecy capacity for a wide range of

wiretap channels under the condition that both main and wire-tap channels are symmetric and binary-input,

and wire-tap channel is degraded with respect to the main channel.

O. Koyluoglu et al.

[46]

2012 It is demonstrated that the polar codes can achieve non-zero perfect secrecy rates for the binary-input

degraded wiretap channel with low encoding-decoding complexity.

E. Sasoglu et al. [47] 2013 A new multi-block polar coding scheme is introduced on top of [45] to resolve the difﬁculty in providing

both strong security and reliability using polar codes.

Y. Zhang et al. [48] 2014 A concatenated coding scheme based on polar codes and LDPC codes for the AWGN wiretap channel is

proposed. Moreover, a transmission scheme using rate compatible Polar-LDPC codes to adapt for different

dynamic environments is also presented.

L. Song et al. [49] 2014 A feedback-based secrecy coding scheme using polar code over wiretap channels is proposed.

R. A. Chou et al. [50] 2015 An alternative approach to the traditional way of generating secret keys is proposed based on polar codes

that jointly deals with reliability and secrecy.

R. A. Chou et al. [51] 2015 A low-complexity and secrecy capacity achieving polar coding scheme is developed for the discrete

memoryless wiretap channel with nearly optimal amount of uniform randomness in the stochastic encoder.

B. Channel-Based Adaptation Transmission [II]

Concept: The starting point of this direction was ﬁrst

inspired and initiated (from basic information-theoretic per-

spective) by Bloch et al. [30], Liang et al. [64], and Gopala et

al. [65], concurrently (in the same year) but independently. In

these works, it was proven that non-zero secrecy rate can be

achieved in a wireless fading environment even when Eve’s

SNR is equal to or higher than Bob’s one on average since

there will always be times where Bob’s instantaneous channel

condition is better than Eve’s one because of the independent

fading phenomena between Alice-to-Bob and Alice-to-Eve

channels. Thus, by designing an optimal or adaptive transmis-

sion scheme, perfect secure communication can be achieved

at a certain rate.

Without loss of generality, this security technique takes its

effective role when the transmitter optimizes or adapts its

transmission parameters according to the wireless fading chan-

nel conditions, location, and requirements of the legitimate

receiver. Since the transmitted signal is set to be optimal for

Bob’s channel, but not anybody else. This essentially results

in a better SNR at Bob compared to Eve, who experiences a

different channel from Bob. Thus, Bob in this case does not

need to perform any extra processing to decode his data. The

basic block diagram of channel-based transmission adaptation

for PLS is presented in Fig. 5. Adaptive transmission based

on legitimate receiver’s CSI requires full or partial channel

knowledge at the transmitter which can be obtained by using

reference sounding signals (used mostly in time division du-

plex (TDD) systems) or by sending explicit frequent CSI feed-

back updates (used mostly in frequency division duplex (FDD)

systems) about the conditions and status of the receiver’s

channel so that the transmitter can adjust (adapt/optimize) its

transmission parameters accordingly.

Beside the feedback related to CSI knowledge at Alice,

there are other important feedbacks, which can be useful for

security such as ACK and NACK messages in ARQ process,

pre-coding matrix indicator (PMI) and rank indicator (RI) in

MISO and MIMO systems, received signal strength indicator

(RSSI), type of application used at user’s side, etc. This

kind of signaling information (i.e., feedback or partial/full

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