Studentische Arbeiten

Titel: Sparse Code Multiple Access for 5G Radio Access
Typ:
  • Masterarbeit
Betreuer:
Status: abgeschlossen

Hintergrund

With the rollout of technology like Internet of Things (IoT), the number of devices to be connected to the Internet is expected to grow exponentially.  A single macrocell in 5G is expected to be able to serve a massive connectivity of machine-type communications along with the traditional high-rate users (smartphone, iPad, etc.). Till now, orthogonal approaches are applied, which means the users are orthogonal in at least one of the following domains: time (TDMA), frequency (FDMA), code (CDMA). Orthogonal approaches allow a simpler receive strategy, but it is not spectral efficient and usually have to be synchronized in time or frequency, which results in signaling overhead.   

Problemstellung

Recently, many non-orthogonal multiple access methods are proposed to meet the 5G requirements. Among various non-orthogonal mutliple access methods, sparse code multiple access (SCMA) has attracted a lot of interest. Compared to orthogonal frequency divison multiple access (OFDMA) in LTE/LTE-A, SCMA can exploit the so-called multiuser gain, making it more spectral efficient. Furthermore, the receiver complexity is limited by the sparsity of overloading.

 

In this work, the basic principles and properties of SCMA will be investigated in terms of complexity and achievable information rates. The performance of this novel mutliple access scheme will be evaluated and compared to traditional orthogonal multiple access methods such as OFDMA and TDMA.

Aufgabe

The tasks of this thesis involve:

  • literature study of SCMA
  • implement of SCMA in Matlab
  • performance evaluation of SCMA (information rates, throughput)
  • compare to OFDMA, TDMA etc.

 

This thesis can be accomplished in German or English.

Anforderung

 

  • Knowledge of signal processing, OFDM
  • Matlab

Kenntnisgewinn

  1. Digital Signal Processing
  2. Multicarrier modulation
  3. Multiple Access Channel/Multiuser detection
  4. Matlab