130 research outputs found
Wireless MIMO Switching: Weighted Sum Mean Square Error and Sum Rate Optimization
This paper addresses joint transceiver and relay design for a wireless
multiple-input-multiple-output (MIMO) switching scheme that enables data
exchange among multiple users. Here, a multi-antenna relay linearly precodes
the received (uplink) signals from multiple users before forwarding the signal
in the downlink, where the purpose of precoding is to let each user receive its
desired signal with interference from other users suppressed. The problem of
optimizing the precoder based on various design criteria is typically
non-convex and difficult to solve. The main contribution of this paper is a
unified approach to solve the weighted sum mean square error (MSE) minimization
and weighted sum rate maximization problems in MIMO switching. Specifically, an
iterative algorithm is proposed for jointly optimizing the relay's precoder and
the users' receive filters to minimize the weighted sum MSE. It is also shown
that the weighted sum rate maximization problem can be reformulated as an
iterated weighted sum MSE minimization problem and can therefore be solved
similarly to the case of weighted sum MSE minimization. With properly chosen
initial values, the proposed iterative algorithms are asymptotically optimal in
both high and low signal-to-noise ratio (SNR) regimes for MIMO switching,
either with or without self-interference cancellation (a.k.a., physical-layer
network coding). Numerical results show that the optimized MIMO switching
scheme based on the proposed algorithms significantly outperforms existing
approaches in the literature.Comment: This manuscript is under 2nd review of IEEE Transactions on
Information Theor
The Approximate Capacity of the Gaussian N-Relay Diamond Network
We consider the Gaussian "diamond" or parallel relay network, in which a
source node transmits a message to a destination node with the help of N
relays. Even for the symmetric setting, in which the channel gains to the
relays are identical and the channel gains from the relays are identical, the
capacity of this channel is unknown in general. The best known capacity
approximation is up to an additive gap of order N bits and up to a
multiplicative gap of order N^2, with both gaps independent of the channel
gains.
In this paper, we approximate the capacity of the symmetric Gaussian N-relay
diamond network up to an additive gap of 1.8 bits and up to a multiplicative
gap of a factor 14. Both gaps are independent of the channel gains and, unlike
the best previously known result, are also independent of the number of relays
N in the network. Achievability is based on bursty amplify-and-forward, showing
that this simple scheme is uniformly approximately optimal, both in the
low-rate as well as in the high-rate regimes. The upper bound on capacity is
based on a careful evaluation of the cut-set bound. We also present
approximation results for the asymmetric Gaussian N-relay diamond network. In
particular, we show that bursty amplify-and-forward combined with optimal relay
selection achieves a rate within a factor O(log^4(N)) of capacity with
pre-constant in the order notation independent of the channel gains.Comment: 23 pages, to appear in IEEE Transactions on Information Theor
Signal Alignment: Enabling Physical Layer Network Coding for MIMO Networking
published_or_final_versio
Multicast Scheduling and Resource Allocation Algorithms for OFDMA-Based Systems: A Survey
Multicasting is emerging as an enabling technology
for multimedia transmissions over wireless networks to support several groups of users with flexible quality of service (QoS)requirements. Although multicast has huge potential to push the limits of next generation communication systems; it is however one of the most challenging issues currently being addressed. In this survey, we explain multicast group formation and various
forms of group rate determination approaches. We also provide a systematic review of recent channel-aware multicast scheduling and resource allocation (MSRA) techniques proposed for downlink multicast services in OFDMA based systems. We study these enabling algorithms, evaluate their core characteristics, limitations and classify them using multidimensional matrix. We cohesively review the algorithms in terms of their throughput maximization, fairness considerations, performance complexities,
multi-antenna support, optimality and simplifying assumptions. We discuss existing standards employing multicasting and further highlight some potential research opportunities in multicast systems
Enhancing wireless security via optimal cooperative jamming
In this work, we analyze the secrecy rate in a cooperative network, where a source node is assisted by relay nodes via cooperative jamming for delivering a secret message to the destination in the presence of an eavesdropper node. We consider the availability of both full and partial channel state information (CSI), and we take into account average power limitation at the relays as we formulate the rate maximization problem as a primal-dual problem. We derive the closed form solution for the full CSI case, and we show that the optimal solution allows the transmission of only one relay. For the partial CSI case, we define the concept of secrecy outage, where some of packets are intercepted by the eavesdropper, and we derive the secrecy outage probability and throughput in terms of average channel statistics. Due to the high nonlinearity of the secrecy throughput term, we propose a gradient update algorithm for obtaining the optimal power solutions for the partial CSI case. Our simulations demonstrate the gains of cooperative jamming over direct transmission for both full and partial CSI cases, where it is shown that the secrecy rate of the direct transmission is increased significantly, by %20−%80, when CJ is employed with our optimal power assignment algorithm
- …