Low complexity user scheduling for multi‐antenna Gaussian broadcast systems with quality of service requirements

Effective Capacity in Wireless Networks: A Comprehensive Survey

“…Multi-hop Mesh Networks [48] Rayleigh Fading Channels Video Applications Video Streaming Mobile Networks [39] Nakagami-m Fading Channels Cross-layer Design [49] Rayleigh Fading Channels Long Term Evolution [50] EPA Fading Channels Cross-layer Design [51] Rayleigh Fading Channels Wireless Cooperative Networks [52] Generalized k Fading Channels Multi-user Video Streaming [53] Correlated Fading Channels Multi-Channel [54] Rayleigh Fading Channels Broadband-ISDN [55] Not Considered Multi-user Video Streaming [56] Rayleigh Fading Channels Wireless Local Area Networks [57] Nakagami-m Fading Channels 5G Networks [58] Nakagami-m Fading Channels FD-Relay Networks [59] Rayleigh Fading Channels Cognitive Radio Networks [60] Nakagami-m Fading Channels 5G Networks [61] Nakagami-m Fading Channels FD-Relay Networks [62] Nakagami-m Fading Channels Femto Cells [63] Not Considered Wireless Local Area Networks [64] DTMC-Based Fading Channels OFDMA-Based Networks [65] Nakagami-m Fading Channels Wireless Local Area Networks [66] Rayleigh Fading Channels Multi-User Video Streaming [67] Rayleigh Fading Channels Multi-User Video Streaming [68] Rayleigh Fading Channels Cross-Layer Design [69] Rayleigh Fading Channels WiMAX [70] Rician Fading Channels Multi-User Video Streaming [71] Not Defined Wireless Virtual Networks [72] Rayleigh Fading Channels OFDMA-Based Networks [73] Rayleigh Fading Channels Wireless Sensor Networks [74] Rayleigh Fading Channels Multi-User Video Streaming [75] Rayleigh Fading Channels Wireless Local Area Networks [76] Not Defined Cross-Layer Network Design [77] Nakagami-m Fading Channels Heterogeneous Wireless Networks [78] Not Defined Cellular Networks [79]…”

Resource allocation for statistical QoS guarantees in MIMO cellular networks

“…This is later used to derive the encoding order based on our heuristic in line (8). Using the encoding order, we now reapply CLT to estimate effective capacities with the effect of interference.…”

“…Also, θ can continuously vary from 0 to ∞, and thus a wide spectrum of QoS constraints can be readily characterized by a general model. However, incorporating the effective capacity model into multi-user communications faces significant challenges, which are not encountered in a single user wireless link [4,[6][7][8][9][10]. Multi-user systems often have to dynamically allocate the wireless resources based on mobile users' channel state information (CSI), and they usually need to balance the performances among all mobile users according to users' diverse QoS requirements.…”