Dear Timothy,

Data can be compressed by two ways:

1-By using loss less compression such as variable length coding, context adaptive variable length coding,Context-based adaptive binary arithmetic coding and other methods. The lossless compression reduced version can be restored completely without any losses.

2- By using higher order modulation techniques such as M qpsk or M qam where every  modulated symbol contains an n-bits with n=log2 n. So, for M=4, n=2 and every symbol contains 2 bits and for M=16, n=4 and the symbol contains 4 bits. So, the symbol rate rs will be rs= rb/n with rb the bit rate. After demodulation we can completely restore the original bit stream.

In the two cases the band width required to transmit the signal will be reduced.

wish you success

Dear Timothy,

Data can be compressed by two ways:

1-By using loss less compression such as variable length coding, context adaptive variable length coding,Context-based adaptive binary arithmetic coding and other methods. The lossless compression reduced version can be restored completely without any losses.

2- By using higher order modulation techniques such as M qpsk or M qam where every  modulated symbol contains an n-bits with n=log2 n. So, for M=4, n=2 and every symbol contains 2 bits and for M=16, n=4 and the symbol contains 4 bits. So, the symbol rate rs will be rs= rb/n with rb the bit rate. After demodulation we can completely restore the original bit stream.

In the two cases the band width required to transmit the signal will be reduced.

wish you success

Dear Timothy.

I agree with the suggestions of mr. Zekry. I would only remind you that with the use of higher order modulation techniques the sensitivity to noise and the system linearity increases. So, In  the real world you may expect some increasing of BER, depending of the above mentioned parameters of the system.

With kind regards,

Milan

The two methods explained by Mr. Zekry are the options for your questions. However, as Mr. Sval told increase in BER is an issue for higher order modulation. In practice a channel coding is used on top of the modulation (in Rx decoder) to reduce the BER further. However, this channel coding will introduce some redundant bits (as parity bits in addition to the information bits) thus bits\hz\sec may decrease. Therefore, you have to compromise between BER and bits\Hz\Sec.

Depending on need generally, it is not possible to retain the same data size after a signal has been compressed and demodulated. The probable reason here being that during demodulation, the undesired carrier elements of the signal is usually filtered out while the information signal is extracted for further processing. However, the carrier elements may be re-injected back if wanted and in that case the signal size may approximate the original data size.

I will want to agree with Mr. Edwin but you said it depend on need generally. However, i do know that the carrier element is still require during demodulation hence the re-injection as you said. If i may ask then is the re-injection optional? because that is the purpose of the carrier recovery circuit and the clock. Thanks

Regards

By using loss less compression such as variable length coding, context adaptive variable length coding,Context-based adaptive binary arithmetic coding and other methods, by lossless Is it possible to compress data in a signal during transmission and still retain its size after demodulation

The Data Compression is a source coding, in which transmission techniques are used to its reliable and efficient delivery, Among the latters, is the modulation; used after an Error Correcting Code or combined.  This ensures that data, through the demodulation and decoding, is recovered with less error. 

thank you all

Hi

You can use Source Coding methods such as:

Huffman Coding, Arithmetic Coding, Run-Length Encoding, Lempel-Ziva and etc.

Good Luck

Hello Timothy

The data compression required will depend on your application. Loss less compression has been well described above, but note that successful use will usually require error free transmission. As this is virtually impossible some error correction is vital. Forward error correction can be used in unidirectional (broadcast) links, but still cannot guarantee that there will be no loss of data. To achieve guaranteed transmission you will need a duplex link with some handshaking protocol. TCP is an example, or Link Access Protocol for telecom signalling.

Further loss less compression will result in a variable length compressed data stream so transmission time will be data dependent. This is OK for file transfers, but not acceptable for say voice where delay variation cannot be tolerated. In this case you would need a lossy fixed rate compression algorithm. This would often be used with forward error correction. Lossy compression will not return the full input data, but an approximation to your signal. Refinements of this approach code more significant parts of the data with more error correction and let less significant parts suffer from a higher BER.

I hope that helps.