417 research outputs found
Minimum-cost multicast over coded packet networks
We consider the problem of establishing minimum-cost multicast connections over coded packet networks, i.e., packet networks where the contents of outgoing packets are arbitrary, causal functions of the contents of received packets. We consider both wireline and wireless packet networks as well as both static multicast (where membership of the multicast group remains constant for the duration of the connection) and dynamic multicast (where membership of the multicast group changes in time, with nodes joining and leaving the group). For static multicast, we reduce the problem to a polynomial-time solvable optimization problem, and we present decentralized algorithms for solving it. These algorithms, when coupled with existing decentralized schemes for constructing network codes, yield a fully decentralized approach for achieving minimum-cost multicast. By contrast, establishing minimum-cost static multicast connections over routed packet networks is a very difficult problem even using centralized computation, except in the special cases of unicast and broadcast connections. For dynamic multicast, we reduce the problem to a dynamic programming problem and apply the theory of dynamic programming to suggest how it may be solved
Energy-Efficient Symbol-Level Precoding in Multiuser MISO Based on Relaxed Detection Region
This paper addresses the problem of exploiting interference among
simultaneous multiuser transmissions in the downlink of multiple-antenna
systems. Using symbol-level precoding, a new approach towards addressing the
multiuser interference is discussed through jointly utilizing the channel state
information (CSI) and data information (DI). The interference among the data
streams is transformed under certain conditions to a useful signal that can
improve the signal-to-interference noise ratio (SINR) of the downlink
transmissions and as a result the system's energy efficiency. In this context,
new constructive interference precoding techniques that tackle the transmit
power minimization (min power) with individual SINR constraints at each user's
receiver have been proposed. In this paper, we generalize the CI precoding
design under the assumption that the received MPSK symbol can reside in a
relaxed region in order to be correctly detected. Moreover, a weighted
maximization of the minimum SNR among all users is studied taking into account
the relaxed detection region. Symbol error rate analysis (SER) for the proposed
precoding is discussed to characterize the tradeoff between transmit power
reduction and SER increase due to the relaxation. Based on this tradeoff, the
energy efficiency performance of the proposed technique is analyzed. Finally,
extensive numerical results show that the proposed schemes outperform other
state-of-the-art techniques.Comment: Submitted to IEEE transactions on Wireless Communications. arXiv
admin note: substantial text overlap with arXiv:1408.470
Coordinated Multicast Beamforming in Multicell Networks
We study physical layer multicasting in multicell networks where each base
station, equipped with multiple antennas, transmits a common message using a
single beamformer to multiple users in the same cell. We investigate two
coordinated beamforming designs: the quality-of-service (QoS) beamforming and
the max-min SINR (signal-to-interference-plus-noise ratio) beamforming. The
goal of the QoS beamforming is to minimize the total power consumption while
guaranteeing that received SINR at each user is above a predetermined
threshold. We present a necessary condition for the optimization problem to be
feasible. Then, based on the decomposition theory, we propose a novel
decentralized algorithm to implement the coordinated beamforming with limited
information sharing among different base stations. The algorithm is guaranteed
to converge and in most cases it converges to the optimal solution. The max-min
SINR (MMS) beamforming is to maximize the minimum received SINR among all users
under per-base station power constraints. We show that the MMS problem and a
weighted peak-power minimization (WPPM) problem are inverse problems. Based on
this inversion relationship, we then propose an efficient algorithm to solve
the MMS problem in an approximate manner. Simulation results demonstrate
significant advantages of the proposed multicast beamforming algorithms over
conventional multicasting schemes.Comment: 10pages, 9 figure
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