CN102104396B - Pulse UWB (Ultra Wide Band) communication system based on CS (Compressed Sensing) theory - Google Patents

Abstract

The invention discloses a pulse UWB (Ultra Wide Band) communication system based on a CS (Compressed Sensing) theory. A digital signal (X) transmitted by a transmitting terminal is effectively observed by introducing signal detection in the CS theory through a sparse algorithm in a digital signal processor, combining a random precoding module added at the transmitting terminal and matching with a pulse generating module, a UWB channel and a low-speed sampler, and a common recovery reconfiguration algorithm in the CS theory is utilized to recover and reconstruct the digital signal (X) and realize communication. In the communication system provided by the invention, a plurality of parallel correlators and low-speed samplers needed in a first parallel scheme are not needed at a receiving terminal so that the problem of high hardware implementation complexity in the parallel scheme is solved; meanwhile, the low-speed sampler is directly used at the receiving terminal for sampling, and an analogue information converter is not used, so that the influence of the causality of a low-pass filter in the analogue information converter on observation is avoided and the problem of sparse observation matrix caused by the causality in a serial scheme is solved.

Description

A kind of pulse ultra-broadband communication system based on the CS theory

Technical field

The present invention relates to pulse ultra-broadband communication system, particularly relate to a kind of pulse ultra-broadband communication system based on the CS theory.

Background technology

Pulse ultra-broad band (Ultra Wideband, referred to as UWB) technology is as a kind of wireless communication technology scheme, with its low complex degree, low cost, high position precision, can share with other system the advantage such as frequency spectrum, in wireless sensor network and hi-Fix and navigation system, have a wide range of applications.As shown in Figure 1, be the structure chart of UWB communication system, comprise transmitting terminal 1, UWB channel 2 and receiving terminal 3.Wherein, transmitting terminal 1 comprises pulse generation module 101, by it, produces the UWB pulse, and digital signal X is transmitted after being loaded on the UWB pulse u (t), sending to receiving terminal 3 by UWB channel 2, receiving terminal 3 comprises radio-frequency front-end 301 and digital signal processor 302, radio-frequency front-end 301 is analogue device, to the received signal r (t)carry out analog (as filtering, relevant, sampling processing, the effect difference of different receiver radio frequency front ends, but be one or more in above-mentioned three kinds of signals processing), send into afterwards in digital signal processor 302 signal is carried out to Digital Signal Processing, obtain the estimating signal X ' of digital signal X, thereby digital signal is passed to receiving terminal from transmitting terminal, completes whole communication process.

Because the UWB communication bandwidth is very large, can reach several GHz, if in said system receiving terminal 3 directly to the received signal r (t) estimated and detected, can bring very large challenge to the system realization: (1), according to nyquist sampling theorem, receiving terminal 3 needs high sample frequency detection signal r (t), this is difficult to analog to digital converter ADC single in digital signal processor 302 and realizes, even realize, analog to digital converter ADC sample frequency is higher also can cause very high system power dissipation; (2) UWB channel multi-path number numerous (can reach hundreds of footpaths), multidiameter is large, this channel characteristic will bring serious intersymbol interference (ISI) to whole communication system, in digital signal processor 302, needs complicated signal processing algorithm to resist ISI.Therefore, in prior art, compressed sensing (Compress Sensing, referred to as CS) theory is incorporated in the UWB communication system, thereby overcomes above-mentioned two challenges.

The CS theory is pointed out, if signal A is compressible or is sparse under certain transform-based, so just can with the incoherent observing matrix of transform-based, signal A be projected on a low-dimensional (M dimension) space and obtain observation signal B by one, then by solving an optimization problem, just can recover with very high probability primary signal A from observation signal B.In prior art, the CS theory is incorporated in the UWB communication system and has two schemes to realize.

The first scheme is called parallel scheme, as shown in Figure 2, at receiving terminal 3, use correlator unit 303(to be formed by M correlator) and low speed sampler unit 304(by M low speed sampler, formed), pulse generation module 101, UWB channel 2, correlator unit 303 and low speed sampler unit 304 are equivalent to the observing matrix under the CS theory, the effective observation of realization to signal X, obtain observation signal Y(i) (i=1,2,3 ... M), in the CS theory by storage in digital signal processor 307, common signal recovery restructing algorithm can recover signal X.This scheme can be resisted intersymbol interference problem ISI, and, without high-speed sampling, still, needs to increase by one group of correlator and one group of low speed sampler in scheme, and the complexity that system hardware is realized is very high, and the cost of communication system and power consumption are also larger.

First scheme is called serial scheme, and as shown in Figure 3, receiving terminal 3 is used analog information transducer 305, and wherein, analog information transducer 305 comprises pseudo-random sequence generator 3051, low pass filter 3052 and low speed sampler 3053.Store algorithm in digital signal processor 306, can be by the signal received r (t)be considered as rarefaction, thereby the input problem is introduced in the CS theory, and pulse generation module 101, UWB channel 2 and analog information transducer 305 are equivalent to the observing matrix under the CS theory, the effective observation of realization to signal X, obtain observation signal Y(i), then in the CS theory by storage in digital signal processor 306, common signal recovery restructing algorithm recovers the signal that receiving terminal 3 receives r (t), and then recover signal X.The complexity that this scheme system hardware is realized is low, but but there are two other shortcomings: 1) because simulation low-pass filter 3052 has causality, these characteristics can make the observing matrix under the CS theory of analog information transducer 305 structure become sparse, thereby reduce the validity of observation station, cause the communication system performance variation; 2) communication system needs the spreading rate of pseudo-random sequence generator 3051 very high, has so also increased system power dissipation.

Summary of the invention

Technical problem to be solved by this invention is: make up above-mentioned the deficiencies in the prior art, a kind of new pulse ultra-broadband communication system based on the CS theory is proposed, can overcome the high problem of hardware implementation complexity in parallel scheme, also can overcome the observing matrix Sparse Problems caused because of causality in serial scheme, the simultaneity factor power consumption is also lower.

Technical problem of the present invention is solved by following technical scheme:

A kind of pulse ultra-broadband communication system based on the CS theory, comprise transmitting terminal, UWB channel and receiving terminal, the packet that described pulse ultra-broadband communication system is to be sent is expressed as digital signal, described digital signal transfers to described receiving terminal from described transmitting terminal by described UWB signal, described receiving terminal is based on the theoretical described digital signal of reconstruct of recovering of CS, described transmitting terminal comprises random precoding module and pulse generation module, described random precoding module is carried out stochastic transformation to described digital signal, obtains the conversion vector, described pulse generation module receiving conversion vector, load on conversion vector in the UWB pulse of its generation and transmitted, described UWB channel receives transmitting of described pulse generation module output, and the output receiving end signal is to receiving terminal, described receiving terminal comprises low speed sampler and digital signal processor, described low speed sampler is sampled to described receiving end signal, the observation signal of output digit signals is to described digital signal processor, store the Sparse Least for described digital signal rarefaction is meaned in described digital signal processor, the equivalent matrix of described random precoding module under the CS theory, the equivalent matrix of described pulse generation module under the CS theory, for estimating the channel estimation method of impulse response of described UWB channel, the derivation algorithm that obtains the equivalent matrix of described UWB channel under the CS theory for deriving according to described impulse response and for recover to reconstruct the recovery restructing algorithm of described digital signal from described observation signal.

The beneficial effect that the present invention is compared with the prior art is:

Pulse ultra-broadband communication system based on the CS theory of the present invention, by the Sparse Least in digital signal processor, input is introduced in the CS theory, the random precoding module increased in conjunction with transmitting terminal, cooperation pulse generation module, UWB channel and low speed sampler are realized the effective observation to the digital signal X of transmitting terminal transmission.Utilize in digital signal processor recovery restructing algorithm commonly used in the CS theory can recover reconstructed number signal X, realize communication.In communication system of the present invention, receiving terminal does not need to need parallel a plurality of correlators and low speed sampler in the parallel scheme of image space case one, has therefore overcome the high problem of hardware implementation complexity in the parallel scheme; Receiving terminal is directly used the low speed sampler to be sampled simultaneously, do not need to use the analog information transducer, also just avoid the impact of the causality of the low pass filter in the analog information transducer on observation, overcome the observing matrix Sparse Problems caused because of causality in serial scheme; Do not need to use pseudo-random sequence generator in simultaneity factor, system power dissipation is also reduced.

The accompanying drawing explanation

Fig. 1 is the structure chart of UWB communication system in prior art;

Fig. 2 in prior art is incorporated into the CS theory parallel scheme structure chart in the UWB communication system;

Fig. 3 in prior art is incorporated into the CS theory serial scheme structure chart in the UWB communication system;

Fig. 4 is the structure chart of the UWB communication system in the specific embodiment of the invention.

Embodiment

Below in conjunction with embodiment and contrast accompanying drawing the present invention is described in further details.

As shown in Figure 4, the UWB communication system architecture figure based on the CS theory in this embodiment, comprise transmitting terminal 41, UWB channel 42 and receiving terminal 43.

Transmitting terminal 41 comprises random precoding module 4101 and pulse generation module 4102.By pulse ultra-broadband communication system, packet to be sent is expressed as digital signal X, and digital signal X is the conversion vector Z through random precoding module 4101 stochastic transformations, is superimposed to subsequently in the UWB pulse that pulse generation module 4102 produces and is transmitted u (t)thereby, launch.

Transmitting of UWB channel 42 received pulse generation module 4102 outputs u (t), the output receiving end signal r (t)to receiving terminal 43.

Receiving terminal 43 comprises low speed sampler 4301 and digital signal processor 4302,4301 pairs of receiving end signals of low speed sampler r (t)sampled, the observation signal Y of output digit signals X is to digital signal processor 4302, store the Sparse Least for digital signal X rarefaction is meaned in digital signal processor 4302, the random equivalent matrix of precoding module 4101 under the CS theory, the equivalent matrix of pulse generation module 4102 under the CS theory, for estimating the channel estimation method of impulse response of UWB channel 42, the derivation algorithm obtain the equivalent matrix of UWB channel 42 under the CS theory for deriving according to impulse response and for recover to reconstruct the recovery restructing algorithm of digital signal X from observation signal Y.

This communication system is observed data-signal X based on the CS theory, and reconstruct requires the sparse of pending signal under the CS theory simultaneously, therefore following minute rarefaction, observation, reconstruct three parts, be described the algorithm of storing in communication system and corresponding digital signal processor 4303.

First: rarefaction

At first data-signal X needs through LS-SVM sparseness, in correspondence system, is to realize by the Sparse Least for rarefaction representative digit signal X of storage in the digital signal processor 4302 in receiving terminal 43.

Sparse Least is specially: set virtual sample frequency fs; In this embodiment, the bit number of the packet that communication system sends is K, the information vector that digital signal X is K * 1 dimension, element take from set 1 ,-1}; The bit rate of packet is f _bit , bit duration is 1/ f _bit ; The duration of the pulse that pulse generation module 4102 produces is tp, the number without overlapping pulse that can hold in packet bit duration be D=1/ ( t _p f _bit ), the virtual sampling number q=adopted in the duration of a pulse t _p f _s ; Digital signal X rarefaction is expressed as:

Wherein, c

?<1 ,-1}, mean transmission information; virtual sample frequency fsneed consider setting according to the requirement of sparse property and the Corresponding Sparse Algorithm computational complexity of digital signal X, make virtual sampled point q is integer simultaneously.Virtual sample frequency fslarger, the sparse property after digital signal X rarefaction is better, and error rate of system is just lower.But the computational complexity of Corresponding Sparse Algorithm and recovery restructing algorithm described later also can increase thereupon, therefore need compromise to consider.

After rarefaction means X, the vector that X is KDq * 1 dimension, only at Dq, 2Dq, 3Dq ... there is numerical value at the K places such as KDq, and all the other positions are 0., and digital signal X is by rarefaction.According to signal theory, arbitrary sparse signal all can be expressed as the product of its sparse base and coefficient vector, so the digital signal after rarefaction also can be expressed as X=ψ θ, and wherein θ is the coefficient vector of digital signal X; ψ=[ ψ ₀, ψ ₁, ψ ₂..., ψ _{Г X-1}] be Г _x* Г _xthe dimension unit matrix, Г _x=KDq.When K<<Г _xthe time, digital signal X is sparse under orthogonal basis ψ, the sparse base that ψ is digital signal X, and coefficient vector θ equals digital signal X.

Second portion: observation

Under the CS theory, after rarefaction means X, need by observing matrix, digital signal X effectively to be observed, obtain observation signal Y, in correspondence system, it is the processing of random precoding module 4101, pulse generation module 4102, UWB channel 42,4301 couples of data-signal X of low speed sampler.Therefore, each module can correspondingly be equivalent to observing matrix to the general effect of the processing operation of digital signal X, therefore in digital signal processor 4302, need respective stored to set the equivalent matrix of each module under the CS theory, thereby the equivalent matrix combination by each module obtains observing matrix, for aftermentioned, recovers reconstruct.

Digital signal X after random 4101 pairs of rarefactions of precoding module carries out stochastic transformation, and it plays vital effect in system, is determining to a great extent the validity of communication system signal observation.In this embodiment, in digital signal processor 4302, its equivalent matrix under the CS theory of storage is set as a stochastic transformation matrix

,

Wherein, i=n * q, n is natural number, 1≤n≤DK; Г _x= kDq; Coefficient a is for adjusting parameter, for regulating the average transmit power of transmitting terminal; In matrix, the value of nonzero element is taken from the once realization of standard Gaussian Profile or takes from the random sequence code.In detail, for example can generate at random Gaussian-distributed variable by the matlab application software, give above-mentioned nonzero element by the value of Gaussian-distributed variable and get final product; Also can extract+1 ,-1 from the random sequence code and give above-mentioned nonzero element.

Carry out the conversion vector Z obtained after stochastic transformation, be Z=

x.

Conversion vector Z input pulse generation module 4102, transmitted u (t).In this embodiment, in digital signal processor 4302, the equivalent matrix of pulse generation module 4102 under the CS theory of storage is set as

,

for Г _x* Г _xmatrix,

Wherein, in matrix

_,

λ ₀=[ p ₀ p ₁... p _q-1] ^tthe virtual vector of samples of UWB pulse within its duration for 4103 generations of pulse generation module.

Equivalent matrix about the UWB channel under the CS theory is to be obtained by the derivation algorithmic derivation.At first the channel estimation method in digital signal processor 4302 estimates to obtain the impulse response h of UWB channel, channel estimation method belongs to algorithm known in this field, at this, do not elaborate, then draw equivalent matrix by the derivation algorithmic derivation, specific algorithm is: the row element that extracts the toeplitz matrix of impulse response h obtains out the equivalent matrix of UWB channel under the CS theory.Equivalent matrix notation by the UWB channel under the CS theory is ,

it is as follows with the relational expression of h,

Wherein,

, symbol in formula

in expression, round; μ= fs△ _t, △ _tfor the sampling time interval of described low speed sampler, described virtual sample frequency of while fs,△ _tvalue make μfor integer.

After above-mentioned setting, under the CS theory, the observing matrix of this communication system structure is

=Ф ₃Ф ₂Ф ₁, observation signal Y is expressed as:

Wherein, wfor noise vector.

Third part: recover reconstruct

After observation, known observing matrix

, the recovery restructing algorithm in combined digital signal processor 4303 can be by data-signal X reconstruct out.By the Maximum Likelihood Detection principle, the recovery restructing algorithm that relates to the CS theory in this communication system can be summed up as the quadratic programming problem that solves a standard.

Definition X ⁺=max (X, 0), X ^?=max (X, 0), X=X ⁺x ^?; Make S=[(X ⁺) ^t, (X ^?) ^t] ^t; Quadratic programming problem is:

Wherein, symbol

the relation that is greater than between representing matrix or vectorial corresponding element; Г _x= kDq; R, g and

_{be respectively:}

;

;

for certain very large numerical value, requirement

>100, as desirable

=1000.

For solving of above-mentioned quadratic programming problem, in prior art, existing multiple ripe algorithm, describe no longer one by one at this.

The as above description of three parts, based on the CS theory, through rarefaction, effectively observe and recover reconstruct, realized that communication system transfers to receiving terminal by digital signal from transmitting terminal.The communication system of this embodiment, can be applicable to such as burst communication occasions such as wireless sensor networks, and when need send information, described system sends burst packet; When not having information to send, system is in resting state.

The pulse ultra-broadband communication system based on the CS theory of this embodiment, increase random precoding module and implement the effective observation to signal, and place it in transmitter terminal, thereby greatly reduce the complexity of receiver.In the receiver end restructing algorithm, by pulse generation module and UWB channel being regarded as to the part of signal observation process in the CS theory, provided the rarefaction representation of raw digital signal, make and utilize the theoretical successful reconstruction signal of CS to become possibility.In communication system, on the one hand, receiving terminal does not need as needing a plurality of correlators and low speed sampler parallel join in parallel scheme, has therefore overcome the high problem of hardware implementation complexity in the parallel scheme; On the other hand, receiving terminal is directly used the low speed sampler to be sampled, do not need to use the analog information transducer, just avoided the impact of the causality of the low pass filter in the analog information transducer on observation yet, overcome the observing matrix Sparse Problems caused because of causality in serial scheme; Moreover, not needing the pseudo-random sequence generator that uses spreading rate very high in system, system power dissipation is also reduced.

Above content is in conjunction with concrete preferred implementation further description made for the present invention, can not assert that specific embodiment of the invention is confined to these explanations.For the general technical staff of the technical field of the invention, make without departing from the inventive concept of the premise some substituting or obvious modification, and performance or purposes identical, all should be considered as belonging to protection scope of the present invention.

Claims (9)

1. the pulse ultra-broadband communication system based on the CS theory, described CS theory is compressive sensing theory; Described system comprises transmitting terminal, UWB channel and receiving terminal, by described pulse ultra-broadband communication system, packet to be sent is expressed as digital signal (X), described digital signal (X) is passed through described UWB transmission to described receiving terminal from described transmitting terminal, described receiving terminal, based on the theoretical described digital signal of reconstruct (X) of recovering of CS, is characterized in that:

Described transmitting terminal comprises random precoding module and pulse generation module, and described random precoding module is carried out stochastic transformation to described digital signal (X), obtains conversion vector (Z); Described pulse generation module receiving conversion vector (Z), will convert in the UWB pulse that vectorial (Z) load on its generation transmitted (u (t));

Described UWB channel receives transmit (u (t)) of described pulse generation module output, and output receiving end signal (r (t)) is to receiving terminal;

Described receiving terminal comprises low speed sampler and digital signal processor, described low speed sampler is sampled to described receiving end signal (r (t)), the observation signal (Y) of output digit signals (X) is to described digital signal processor, store the Sparse Least for described digital signal (X) rarefaction is meaned in described digital signal processor, the equivalent matrix of described random precoding module under the CS theory, the equivalent matrix of described pulse generation module under the CS theory, for estimating the channel estimation method of impulse response (h) of described UWB channel, the derivation algorithm obtain the equivalent matrix of described UWB channel under the CS theory for deriving according to described impulse response (h) and for recover to reconstruct the recovery restructing algorithm of described digital signal (X) from described observation signal (Y).

2. the pulse ultra-broadband communication system based on the CS theory according to claim 1 is characterized in that: described Sparse Least realizes by setting virtual sample frequency, and setting virtual sample frequency is fs; The bit number of described packet to be sent is K, and bit rate is f _bit, the duration of the pulse that described pulse generation module produces is Tp, described digital signal (X) rarefaction is expressed as:

Wherein, { 1 ,-1}, mean transmission information to c ∈; The number without overlapping pulse that can hold in the bit duration that D is described packet, D=1/ (T _pf _bit); The virtual sampling number of adopting in the duration that q is a described pulse, q=T _pf _s; Described virtual sample frequency fs considers setting according to the requirement of sparse property and the described Sparse Least computational complexity of described digital signal X, and it is integer that the value of described virtual sample frequency fs of while makes virtual sampled point q.

3. the pulse ultra-broadband communication system based on the CS theory according to claim 2, it is characterized in that: the equivalent matrix of the described random precoding module of storing in described digital signal processor under the CS theory is Φ ₁,

Wherein, i=n * q, n is natural number, 1≤n≤DK; Г _x=KDq; Factor alpha is for adjusting parameter, for regulating the average transmit power of described transmitting terminal; In matrix, the value of nonzero element is taken from the once realization of standard Gaussian Profile or takes from the random sequence code.

4. the pulse ultra-broadband communication system based on the CS theory according to claim 3, it is characterized in that: the equivalent matrix of described pulse generation module under the CS theory of storing in described digital signal processor is Φ ₂, Φ ₂for Г _x* Г _xmatrix,

Wherein, in matrix $\mathrm{\&Omega;}=\left[\begin{array}{cccc}{\mathrm{\&lambda;}}_0,& 0,& ...,& 0\end{array}\right]={\left[\begin{array}{cccc}{p}_0& 0& ...& 0\\ p_1& 0& ...& 0\\ .& & & .\\ .& & & .\\ .& & & .\\ p_{q-1}& 0& ...& 0\end{array}\right]}_{q\&times;q}$ ，

λ ₀=[p ₀p ₁p _q-1] ^tthe virtual vector of samples of UWB pulse within its duration for described pulse generation module generation.

5. the pulse ultra-broadband communication system based on the CS theory according to claim 4, it is characterized in that: the derivation algorithm of storing in described digital signal processor is specially: the row element that extracts the toeplitz matrix of described impulse response h obtains the equivalent matrix Φ of described UWB channel under the CS theory ₃, both relational expressions are as follows:

${\mathrm{\&Phi;}}_3=\left[\begin{array}{cccccccc}h\left(0\right)& 0& ...& 0& ...& 0& ...& 0\\ h(\mathrm{\&mu;}/f_s)& h((\mathrm{\&mu;}-1)/f_s)& ...& h\left(0\right)& ...& 0& ...& 0\\ .& .& & .& & .& & .\\ .& .& & .& & .& & .\\ .& .& & .& & .& & .\\ h(\mathrm{\&rho;\&mu;}/f_s)& h((2\mathrm{\&mu;}-1)/f_s)& ...& & ...& & ...& h((\mathrm{\&rho;\&mu;}-{\mathrm{\&Gamma;}}_X+1)/f_s)\\ .& .& & .& & & & .\\ .& .& & .& & & & .\\ .& .& & .& & & & .\\ 0& 0& ...& 0& ...& h(({\mathrm{\&Gamma;}}_X-1)/f_s)& ...& h(((M-1)\mathrm{\&mu;}-{\mathrm{\&Gamma;}}_X+1)/f_s)\end{array}\right]$

Wherein,

, symbol in formula

?

in expression, round; μ=fs △ _t, △ _tfor the sampling time interval of described low speed sampler, described virtual sample frequency fs, △ _tvalue to make μ be integer.

6. the pulse ultra-broadband communication system based on the CS theory according to claim 5, it is characterized in that: the recovery restructing algorithm of storing in described digital signal processor is summed up as the quadratic programming problem of the standard of solving.

7. the pulse ultra-broadband communication system based on the CS theory according to claim 6, it is characterized in that: the quadratic programming problem of described standard is: definition X ⁺=max (X, 0), X ^?=max (X, 0), X=X ⁺x ^?; Observation vector Y=Φ ₃Φ ₂Φ ₁x+W=Φ X+W; Make S ^?=[(X ⁺) ^t, (X ^?) ^t] ^t; Quadratic programming problem is:

Wherein, symbol

the relation that is greater than between representing matrix or vectorial corresponding element; Г _x=KDq; R, g and ε are respectively: $R=\left[\begin{array}{cc}{\mathrm{\&Phi;}}^T\mathrm{\&Phi;}& -{\mathrm{\&Phi;}}^T\mathrm{\&Phi;}\\ -{\mathrm{\&Phi;}}^T\mathrm{\&Phi;}& {\mathrm{\&Phi;}}^T\mathrm{\&Phi;}\end{array}\right]$ ； $g={[-Y^T\mathrm{\&Phi;},Y^T\mathrm{\&Pi;}]}^T$ ；

β is greater than 100 numerical value.

8. the pulse ultra-broadband communication system based on the CS theory according to claim 1 is characterized in that: described communication system applications is in the burst communication occasion, and when need send information, described system sends burst packet; When not having information to send, system is in resting state.

9. the pulse ultra-broadband communication system based on the CS theory according to claim 8, it is characterized in that: described burst communication occasion is wireless sensor network.

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