- 學位論文
混音編碼傳輸於數位廣播系統之應用
Applying Voice Encoded Multiplexing in DAB System
摘要
在無線通訊環境中，頻寬資源為最重要的資源之一，因此，如何減少射頻頻寬的使用度將為未來重要的討論議題。一種嶄新的訊號處理方式可應用於現今之無線通訊環境中，此種訊號處理方式，能達到在一對傳輸線上或一個頻道上，同時傳送多種訊號，並使其頻寬不但不因訊號種類的增減而增減，反而可以達到自由控制之目的，若將此種訊號處理方式應用於數位廣播系統，則不僅能節省基頻頻寬，更能在同樣的射頻頻寬中，撥放更多的數位廣播節目。因此，在這篇論文中，我們將此種訊號處理方式應用於數位廣播系統，討論整個系統之效能。 本篇論文不僅以軟體平台模擬此一技術之正確性，更以硬體數位訊號處理器實作此技術之可行性，而模擬與實作之訊號來源皆以語音呈現，因此，此技術在此命名為”混音編碼傳輸”。在本篇論文所模擬之環境中，以五個語音訊號輸入為範例，我們可將其五個輸入訊號混合並壓縮於一窄頻帶傳輸後仍能保持各個訊號之正交性，並壓縮於1KHz左右之頻寬，且頻率範圍為我們所自由選擇控制的。在數位廣播系統中，每申請一張執照可獲得1.536MHz的頻寬，最多可播送6個廣播節目，將”混音編碼傳輸”應用於數位廣播系統後，系統之錯誤率效能並不會受到影響，在訊號雜訊比達12dB時，位元錯誤率依然能接近10-5，且每一節目之頻寬可將5個語音節目混合送出，以頻寬1.536MHz計算，則可撥放之語音節目數量可從6個提升至30個，整體收益可提升5倍。
並列摘要
In wireless communications, bandwidth is the most important resource. In the future, how to reduce the usage of radio frequency bandwidth will be an important issue to be discussed. A new signal process method is proposed to be used in wireless communication system and which could mix multi-signals in a narrowband bandwidth. If this method is applied in DAB system, the number of programs would be increased with the same bandwidth. In this thesis, not only the software simulation but also the hardware implementation is presented to prove the feasibility of this proposed signal process method called “voice encoded multiplexing”. In the simulation results, 5 voice signals can be mixed in a 1KHz bandwidth, and the encoded signal of each voice signal has its own orthogonal property. In DAB system, 6 programs most can be transmitted in 1.536MHz bandwidth. However, by applying voice encoded multiplexing in DAB system, 5 programs can be multiplexed in the bandwidth of one program, and the BER performance could approach 10-5 when the SNR is 12dB which is the same as original DAB system. For DAB system, per 1.536MHz bandwidth of one license, we could transmit 30 programs, and the total earnings was 5 times of original DAB system.
參考文獻
延伸閱讀
- 鍾震翰（2011）。應用混合編碼技術處理多頻道之生醫訊號壓縮〔碩士論文，國立臺灣大學〕。華藝線上圖書館。https://doi.org/10.6342/NTU.2011.01759
- 梁孟崴（2019）。混合式類比與數位訊號檢測於巨量多輸入多輸出系統〔碩士論文，國立暨南國際大學〕。華藝線上圖書館。https://doi.org/10.6837/ncnu201900159
- 鍾淮棋（2012）。應用盲點來源分離演算法分解數位助聽器中的混合語音訊號〔碩士論文，國立臺灣大學〕。華藝線上圖書館。https://doi.org/10.6342/NTU.2012.03160
- Chen, W. C. (2019). Deep Learning Applied to Speech and Audio Signal Processing under Adverse Environments [master's thesis, National Tsing Hua University]. Airiti Library. https://www.airitilibrary.com/Article/Detail?DocID=U0016-0206202016161204
- 李哲安（2020）。On the Implementation of Singing Voice Separation on Edge Devices〔碩士論文，國立臺灣大學〕。華藝線上圖書館。https://doi.org/10.6342/NTU202100183