09-07-2012, 11:39 AM
Utility-Optimal Multi-Pattern Reuse in Multi-Cell Networks
[attachment=27233]
Abstract:
Achieving sufficient spatial capacity gain through the use of small cells requires careful consideration of inter cell interference (ICI) management via BS power coordination coupled with user scheduling inside cells. Optimal algorithms are known to be difficult to implement due to high computation and signaling overhead.
This study proposes joint pattern-based ICI management and user scheduling algorithms that are practically implementable. The key idea is to decompose the original problem into two sub-problems in which ICI management is run at a slower time scale than user scheduling. We empirically show that even with such a slow tracking of system dynamics at the ICI management part, the decomposed approach achieves a considerable performance increase compared to conventional universal reuse schemes.
Algorithm
User scheduling, time-scale decomposed algorithm
Explanation
The algorithm based on time-scale decomposition stems from a design rationale in which ICI management may not have to track fast dynamics, e.g., a fast fading channel condition. Instead, it may suffice to run the ICI management scheme following only macroscopic network changes, e.g., user loads/locations, and their average channel conditions. In spite of such slow tracking of system dynamics in ICI management, with the proposed decomposed algorithms,
Existing System
Another important issue in Existing multi-cell networks is to resolve load balance problem between cells. Several investigations explicitly balance the load by changing user associations from the BS in hot-spot cells to an adjacent BS that is less crowded.
Proposed System
proposed to accommodate users in different channel conditions with different reuse factors. However, these a-priori hand-crafted schemes are still far from optimal in the sense that they do not adapt to dynamic network environments, e.g., time-varying user loads/locations. In addition, user scheduling working opportunistically based on perceived time-varying channels must be considered in conjunction with ICI management to achieve a high performance gain.
This complexity reduction for implement ability comes at the cost of a performance gap with the joint optimal algorithm. This is due to the fact that the ICI management part in the decomposed algorithm cannot fully exploit instantaneous inter-cell channel variations; hence, only intra-cell channel variations are opportunistically utilized. Note that in the joint optimal algorithm, both pattern selection and user scheduling fully exploit both inter-cell and intra-cell time-varying channel conditions at a fast time scale.
[attachment=27233]
Abstract:
Achieving sufficient spatial capacity gain through the use of small cells requires careful consideration of inter cell interference (ICI) management via BS power coordination coupled with user scheduling inside cells. Optimal algorithms are known to be difficult to implement due to high computation and signaling overhead.
This study proposes joint pattern-based ICI management and user scheduling algorithms that are practically implementable. The key idea is to decompose the original problem into two sub-problems in which ICI management is run at a slower time scale than user scheduling. We empirically show that even with such a slow tracking of system dynamics at the ICI management part, the decomposed approach achieves a considerable performance increase compared to conventional universal reuse schemes.
Algorithm
User scheduling, time-scale decomposed algorithm
Explanation
The algorithm based on time-scale decomposition stems from a design rationale in which ICI management may not have to track fast dynamics, e.g., a fast fading channel condition. Instead, it may suffice to run the ICI management scheme following only macroscopic network changes, e.g., user loads/locations, and their average channel conditions. In spite of such slow tracking of system dynamics in ICI management, with the proposed decomposed algorithms,
Existing System
Another important issue in Existing multi-cell networks is to resolve load balance problem between cells. Several investigations explicitly balance the load by changing user associations from the BS in hot-spot cells to an adjacent BS that is less crowded.
Proposed System
proposed to accommodate users in different channel conditions with different reuse factors. However, these a-priori hand-crafted schemes are still far from optimal in the sense that they do not adapt to dynamic network environments, e.g., time-varying user loads/locations. In addition, user scheduling working opportunistically based on perceived time-varying channels must be considered in conjunction with ICI management to achieve a high performance gain.
This complexity reduction for implement ability comes at the cost of a performance gap with the joint optimal algorithm. This is due to the fact that the ICI management part in the decomposed algorithm cannot fully exploit instantaneous inter-cell channel variations; hence, only intra-cell channel variations are opportunistically utilized. Note that in the joint optimal algorithm, both pattern selection and user scheduling fully exploit both inter-cell and intra-cell time-varying channel conditions at a fast time scale.