Multiuser Detection
LAMAN: load adaptable MAC for ad hoc networks
EURASIP Journal on Applied Signal Processing
Traffic-aided multiuser detection for random-access CDMA networks
IEEE Transactions on Signal Processing
Fast antenna subset selection in MIMO systems
IEEE Transactions on Signal Processing
Opportunistic beamforming using dumb antennas
IEEE Transactions on Information Theory
Exploiting decentralized channel state information for random access
IEEE Transactions on Information Theory
Stability and delay of finite-user slotted ALOHA with multipacket reception
IEEE Transactions on Information Theory
IEEE Communications Magazine
Multiuser soft interference canceler via iterative decoding for DSL applications
IEEE Journal on Selected Areas in Communications
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Research on scheduling in MIMO multiple access systems is traditionally carried out from an information-theoretic point of view. Such information-theoretic approaches are feasible in homogeneous systems where, although channel fading is assumed, all terminals use the same modulation format, channel coding scheme, data transmission rate, packet lengths and no traffic issues are considered. In these systems, to select the set of terminals that maximize the instantaneous sum capacity leads to the highest system throughput. Unfortunately, in heterogeneous systems this assumption is not always true. Consequently, there is a need to evaluate the effects of such heterogeneity from a network point of view. In this paper, following a cross-layer approach, a generalized model for scheduling in MIMO multiple access is presented. Such model allows to evaluate the effects of heterogeneity on system throughput. Particularly, this generalized model accommodates any kind of heterogeneity from multiuser diversity due to channel fading to heterogeneity due to different data transmission rates. Different scheduling policies are analyzed under this generalized model and further applied to a sensor network. The results obtained are useful to achieve practical insight of such scheduling policies.