利用干扰器状态信息的DS-BPSK接收机性能分析

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本研究论文《性能分析：子优化软判决DS-BPSK接收器在脉冲噪声和连续波干扰下的应用》主要关注在加性白噪声环境中，对直接序列（DS）扩频、二进制相移键控（BPSK）信号的接收问题。研究未考虑自动增益控制（AGC），而是采用了一种系统理论的方法来分析接收机性能，并且对先前的相关文献进行了详尽的回顾。在论文中，作者Juhani Juntti，隶属于奥卢大学电气与信息工程系，专注于探讨在受到脉冲噪声和连续波（CW）干扰的情况下，如何利用干扰器状态信息来改进DS-BPSK接收器的性能。这种子优化的软判决解调方法旨在在复杂通信环境下提高信号检测的精确性和抗干扰能力。通过分析接收器的理论模型，论文可能会深入探讨不同接收策略（如利用干扰器状态估计误差、信噪比改善算法等）对误码率（BER）、符号错误率（SER）或接收信号质量的影响。接收器分析通常涉及信道特性建模、噪声处理、解调算法优化以及对抗干扰的策略。在本研究中，可能涉及到以下关键知识点： 1. **DS-BPSK信号模型**：理解DS-BPSK的基本原理，包括信号编码、扩频过程和传输特性。 2. **脉冲噪声和连续波干扰模型**：区分这两种不同类型干扰的特点，如脉冲噪声的突发性和CW干扰的持续存在，以及它们如何影响信号的接收。 3. **软判决解调**：解释软判决解调的原理，与硬判决解调相比，它如何通过概率估计而不是简单的阈值比较来提高性能。 4. **干扰器状态信息的利用**：讨论如何通过实时获取和处理干扰器的信息，如功率、频率和相位特性，来调整接收器参数，减少其影响。 5. **性能评估**：使用BER、SER等指标衡量接收器在不同干扰条件下的性能，分析子优化策略对这些指标的影响。 6. **系统理论在接收机分析中的应用**：介绍如何运用系统理论工具，如滤波器设计、均衡技术等，来增强接收系统的稳健性。 7. **仿真与实验结果**：文中可能包含了实际的仿真结果和实验验证，展示子优化软判决DS-BPSK接收器在具体应用场景中的性能提升。 8. **结论与未来工作**：论文最后可能会总结研究成果，指出潜在的研究方向，以及在实际通信系统中如何进一步优化接收器性能。这篇论文提供了一个深入理解DS-BPSK接收器在有干扰环境中的性能优化策略的框架，对于无线通信系统设计者和研究人员来说，具有重要的参考价值。

SNR

signal-to-noise ratio in jamming channel (E

)

SNR

signal-to-noise ratio in AWGN channel (E

)

SNR

tot

total signal to noise ratio (E

tot

)

TOPSIM Torino Polytecnico Simulator, communication system simulation

program

information bit duration, second

chip duration, second

channel symbol duration, second

t error correcting capability of a block code

t time

u output of the chip combiner

lower threshold of chip combiner output in AWGN channel

upper threshold of chip combiner output in AWGN channel

lower threshold of chip combiner output in jamming

upper threshold of chip combiner output in jamming

Q(x) 1-erfc(x/2), erfc=complementary error function

)(

zq jamming state probability on the symbol decision time,

where z

is the side information related to these symbols

)(Zq

jamming state sequence probability, z is the side information

sequence related to these symbols

w(x,

) the number of places where Nnx

,...,2,1,x

≠

noise jamming signal bandwidth

spread spectrum signal bandwidth

WGN white gaussian noise

x(t) transmitted data function

x transmitted bit

x coded symbol sequence

n:th element of the code sequence x

the effect of the information in the output of chip combiner

y(t) received signal

y received signal

y channel output code sequence

n:th element of the code sequence y

demodulator output when there is jamming in the channel

z jammer state random variable

Z the group of the integer numbers

z side information sequence

i:th element of the sequence z

phase difference between jamming and information signal

parameter to be optimized in Chernoff bound

noise variance

ν auxiliary variable

probability that a code symbol is affected by jamming

erasing threshold

angular frequency of the information signal, 2

angular frequency of the jamming signal, 2

Contents

Abstract

Preface

List of original papers

List of symbols and abbreviations

Contents

1 Introduction ...................................................................................................................17

1.1 Background, motivation and aim of the thesis........................................................17

1.2 System description..................................................................................................18

1.2.1 Interleaving techniques.................................................................................... 22

1.2.2 Automatic gain control .................................................................................... 24

1.2.3 Interference cancellation..................................................................................24

1.3 Author’s contribution..............................................................................................25

1.4 Outline of the thesis................................................................................................26

2 Decision metrics ............................................................................................................29

2.1 Coding channel model............................................................................................29

2.2 Literature review ....................................................................................................32

2.2.1 Decision metrics ..............................................................................................32

2.2.2 Side information ..............................................................................................37

2.3 Coded bit error rate bound......................................................................................39

3 Communication system model ......................................................................................42

3.1 Jamming signals .....................................................................................................44

3.2 Communication system in jamming .......................................................................45

3.2.1 CW jamming.................................................................................................... 46

3.2.2 Channel symbol and coded bit error probabilities ........................................... 50

4 Hard decision receiver...................................................................................................52

4.1 Decision metric and channel parameter.................................................................. 52

4.2 Performance in jamming ........................................................................................53

5 Soft decision receiver .................................................................................................... 61

5.1 Optimum soft decision receiver, known jammer state............................................61

5.1.1 Decision metric and channel parameter........................................................... 61

5.1.2 Performance in jamming..................................................................................62

5.2 Soft decision receiver, unknown jammer state .......................................................67

5.2.1 Decision metric and channel parameter........................................................... 67

5.2.2 Performance in jamming..................................................................................69

6 Quantized Soft Decision Limiter Receiver....................................................................73

6.1 Decision metric and channel parameter.................................................................. 73

6.2 Performance in jamming ........................................................................................75

7 Signal Level Based Erasure Receiver............................................................................ 81

7.1 Decision metric and channel parameter.................................................................. 81

7.2 Performance in jamming ........................................................................................85

8 Chip Combiner Receiver ...............................................................................................93

8.1 Decision metric and channel parameter.................................................................. 93

8.2 Performance in jamming ........................................................................................96

9 Comparison of the Receivers....................................................................................... 109

9.1 Pulsed noise jamming...........................................................................................109

9.2 Pulsed CW jamming............................................................................................. 116

10 Discussion and Conclusions ...................................................................................... 125

10.1 Discussion...........................................................................................................125

10.2 Conclusions ........................................................................................................126

10.3 Future research directions...................................................................................129

References

Appendices

1 Introduction

1.1 Background, motivation and aim of the thesis

In some cases communication systems are required to operate over a channel that is

affected by intentional jamming, especially against military systems. The jamming signal

may also be another user in the same communication system or another communication

system causing unintentional jamming. The jamming signals may have different

waveforms: noise, continuous wave, modulated, pulsed, or continuous signal. The

jammer cause severe performance degradation for all types of uncoded communication

systems ([1] Vol. 1 p. 148-151). In some cases jamming converts an exponential

dependency of the bit error rate on the signal-to-jamming ratio into a linear one on

logarithmic scale.

The use of a spread-spectrum modulation with error correcting coding is an effective

technique to combat the effects of jamming ([1] Vol. 1 p. 151-167). Usually hard or soft

decision metrics in receivers are studied for coded anti-jam systems. Jammer state

information may be measured from received signal and it can be used with both metrics.

The soft decision metrics outperform hard decision metrics in an additive white Gaussian

noise (AWGN) channel, but in jamming soft decision decoders either require jammer

state information, or must have some method to obtain information concerning the

reliability of received code symbols for satisfactory performance [1 Vol. 1, p. 157-160].

Often it is enough to know if the received symbol was jammed or not jammed. It is

shown, that soft decision metric can give better performance if reliable jammer state

information is available. The measurement of the jammer state information is studied in

this thesis. An effective soft decision metric was studied in the original Papers III and VI

for a direct sequence spread spectrum system with binary phase shift keying (DS/BPSK)

operating in the presence of pulsed jamming. If jammer state information is not available,

one should use the hard decision metric, because the use of the soft decision metric may

lead poor performance in some jamming cases. The hard decision metric is robust and

very simple to implement.

In the area of cellular communication a lot of research work has been done in recent

years to optimize system performance in a very dense signal environment. Many

multiuser interference cancellation and multiuser detection techniques have been

proposed. These techniques are often very complex to implement and in many cases

jamming signals are assumed to be known. The receiver structures studied in this thesis

assume no knowledge of the jamming signal and are simple to implement. They are not

so effective against known interference, but work well in most cases. They can be

considered to be robust receiver structures. The presented methods can be used in many

situations including cellular communications to reduce the effect of interference. One

goal of the study was to find out robust, simple receiver structure in jamming

environment.

The interference cancellation techniques are proposed to be used in spread spectrum

systems to combat the effect of the jamming and interference (e.g. [2] pp. 291-333).

These techniques are still expensive to implement if chip rate of the signal is high. Hybrid

FH/DS systems are even more demanding while the adaptation time of the receiver is

short. It is thus important to optimize receiver structure in jamming without interference

cancellation techniques.

In this thesis binary phase shift keying (BPSK) modulation is considered, but a similar

type of analysis could be done for other coherent phase and frequency modulation

techniques. The metrics must be modified to fit the modulation method. For non-coherent

modulations metrics are different and the analysis is different, because the effect of the

noise and interference in receiver output differs from that of coherent demodulation [3],

[4]. Also mentioned ad hoc metrics are specially designed to be used in BPSK

demodulated systems. In reference [5] differential phase shift keying (DPSK) modulated

systems are analyzed.

In this thesis quantization of the signals are modeled in the receivers. Automatic gain

control (AGC) is assumed to be perfect. The DS/BPSK receivers are studied within a

pulsed jamming channel with the assumption of no fading. The bits are assumed to be

jammed independently, which can be implemented using interleaving techniques.

1.2 System description

In basic detection theory [6], ([7] p. 105-117), the optimal receiver in an AWGN channel

is shown to be a parallel bank of matched filters (MF). In the case of BPSK modulation

only one MF or a correlation receiver is needed. If noise is Gaussian but not white, the

use of a whitening filter before the MF forms the optimum receiver. If the noise is non-

Gaussian, the optimum receiver becomes difficult to implement. Reference [8] presents

the optimum receiver in the case of a summed sine wave and noise. Thus, non-optimal

receivers are often used for simplicity. This has lead to the use of interference

cancellation techniques, which are shortly reviewed in Section 1.2.3. The approach in this

thesis is to consider decision-making techniques to improve a receiver’s performance.

References [9], [10], [11], and [12] discuss the analysis of DS/BPSK systems in the

presence of pulsed jamming. The analysis is well summarized in reference ([1] Vol. 2 p.

3-60). Most of the receivers analyzed in this thesis are presented in the previously

mentioned references. Because in this thesis notations and receiver structures are a little

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