Throughput versus fairness tradeoff analysis

Abstract

Optimal resource allocation is an outstanding issue in wireless communication systems. In this work we focus on the ever challenging optimization of the tradeoff between throughput and fairness. Specifically, we propose a novel framework to analytically derive the maximum average throughput versus fairness under the assumptions that the throughput of each user i) increases if more resources are allocated to him and ii) depends on how many resources and not which resources are allocated. We achieve a general formulation of the tradeoff optimization problem and we also derive and validate a closed form solution in those scenarios where throughput linearly depends on resources, which cover several realistic cases. Besides these valuable results, the framework also lays solid basis toward a more general solution.

Optimal Linear Precodings for Multi-Color, Multi-User Visible Light Communication System with Fairness Considerations

“…where f is the objective function that represents the performance measure of interest. Obviously, criterions such as α-Fair fairness can be used to measure the system performance [46][47][48][49][50][51]. However, the conclusion about how to allocate resources can not directly used in VLC systems due to the special constraints in (20) (21) and (23).…”

Optimization of LTE radio resource block allocation for maritime channels

“…The two basic fundamental assumptions [17] regarding our allocation method are : a) Throughput perceived by any user j from the connected eNodeB i is a function of how many resource element has been allocated rather than what those resources are, b) Throughput increases strictly for a user if more resources are allocated to it.…”

“…In addition to this formulation, Karush-Kuhn-Tucker (KKT) conditions [18], which are detailed for such problems in [17], [19], holds a strong duality. Therefore, the solution attained in primal form is equal to the dual form.…”

“…2) Round Robin Method: The round robin allocation method is formulated in such a way that the same amount of resources are given to all users. In this scenario, a user j perceives the throughput proportional to the one that is possible using all resources [17]. Therefore for a user j , the throughput T ij is given by :…”

“…3) Opportunistic method: For the opportunistic case, we formulate the problem as a maximization problem [17] in such a manner that each eNodeB allocates maximum RBs to a high throughput link as compared to low throughput links, thus increasing the network throughput non uniformly among users. In the problem formulation, however, the constraint space will remain the same as the max-min method described earlier.…”