In future fourth generation wireless networks OFDM and MIMO techniques will be heavily exploited to provide connectivity to heterogeneous users offering different data traffic types. This paper proposes a low complexity resource allocation strategy for MIMO-OFDMA (Multiple-Input Multiple-Output Orthogonal Frequency Division Multiple Access) broadcast channel to support delay-sensitive traffic with heterogeneous rate constraints. The objectives of the scheduler are to maximize the sum-rate on the radio channel, to ensure a fair allocation of resources among users according to given rate constraints, to consider the dynamics of traffic flows by means of weights related to the queue status. The reduction in system complexity is obtained by resorting to opportunistic beamforming for spatial scheduling and by developing an on-line algorithm within a dual optimization framework. Starting from the solution of ergodic sum-rate optimization with rate and power constraints, a new allocation algorithm, where resources are allocated to users according to the achievable rate and to suitable weights that account for the queue status and rate constraints, is proposed. It is shown that this algorithm is able to allocate resources according to rate and fairness constraints of each different traffic class, and to reduce the delays in the queues, even in presence of different channels conditions. ©2011 IEEE.
A low complexity scheduler for multiuser MIMO-OFDMA systems with heterogeneous traffic
TRALLI, Velio;
2011
Abstract
In future fourth generation wireless networks OFDM and MIMO techniques will be heavily exploited to provide connectivity to heterogeneous users offering different data traffic types. This paper proposes a low complexity resource allocation strategy for MIMO-OFDMA (Multiple-Input Multiple-Output Orthogonal Frequency Division Multiple Access) broadcast channel to support delay-sensitive traffic with heterogeneous rate constraints. The objectives of the scheduler are to maximize the sum-rate on the radio channel, to ensure a fair allocation of resources among users according to given rate constraints, to consider the dynamics of traffic flows by means of weights related to the queue status. The reduction in system complexity is obtained by resorting to opportunistic beamforming for spatial scheduling and by developing an on-line algorithm within a dual optimization framework. Starting from the solution of ergodic sum-rate optimization with rate and power constraints, a new allocation algorithm, where resources are allocated to users according to the achievable rate and to suitable weights that account for the queue status and rate constraints, is proposed. It is shown that this algorithm is able to allocate resources according to rate and fairness constraints of each different traffic class, and to reduce the delays in the queues, even in presence of different channels conditions. ©2011 IEEE.I documenti in SFERA sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
