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In this paper, we consider the joint multicast and unicast beamforming design problem in the multi-input single-output downlink wireless network, where all base stations (BSs) potentially can cooperate (as a single virtual BS) to transmit a common multicast and multiple dedicated unicast data streams at the same time on the same frequency band. To reduce cooperation overhead (among different BSs),...
In this paper, we consider a wireless network with one full-duplex (FD) base station (BS) and a set of half-duplex (HD) user equipments (UEs). In such scenario, in addition to the self-interference, the co-channel interference from uplink UEs to downlink UEs is the main bottleneck for the network performance. To overcome this, we consider the problem of maximizing the minimum fairness rate among all...
Point-based value iteration methods are a class of effective algorithms for solving POMDP model. Although MDP-based algorithms such as FSVI can reduce the complexity and improve efficiency greatly by using the optimal strategy of the underlying MDP, the excessive randomness of these algorithms makes them not suitable for the realistic POMDP problems. A probabilistic greedy search value iteration algorithm...
Point-based value iteration methods are a class of effective algorithms for solving POMDP model. However, most of these algorithms explore the belief point set by single heuristic criterion, thus limit the effectiveness. A value iteration algorithm (HHVI) based on hybrid heuristic criteria for exploring belief points set is presented in the paper. HHVI maintains the upper and lower bounds on the value...
The exponential growth of the size of the search space has always been an obstacle to POMDP planning. Heuristics are often used to reduce the search space size and improve computational efficiency. As the advantage of the feature of POMDP problems should be taken into deeper consideration, we analyze the clustering feature of reachable space of POMDP problems and apply policy iteration based on this...
Extensive approximate dynamic programming (ADP) algorithms have been developed based on policy iteration. For policy iteration based ADP of deterministic discrete-time nonlinear systems, existing literature has proved its convergence in the formulation of undiscounted value function under the assumption of exact approximation. Furthermore, the error bound of policy iteration based ADP has been analyzed...
The exact value iteration for POMDP planning is so complex that we use approximation to solve the problems in practice. In recent years, point-based algorithm has become a research hotspot. PBVI algorithm selects successors that improve the worst case density as rapidly as possible. The smaller the gaps between all belief points, the faster the value function converges to the optimal solutions. PBVI...
Complex motion makes consecutive frames experience dramatic change, and thus becomes a barrier to object-tracking. Three factors contribute to more complexity of motion: longer sampling period,an moving object with complex appearance and nonrestraint movement, occlusion, which causes mean shift algorithm losing its target due to too low a Bhattacharyya coefficient. To treat it, mean shift algorithm...
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