7 research outputs found
Outage Constrained Robust Secure Transmission for MISO Wiretap Channels
In this paper we consider the robust secure beamformer design for MISO
wiretap channels. Assume that the eavesdroppers' channels are only partially
available at the transmitter, we seek to maximize the secrecy rate under the
transmit power and secrecy rate outage probability constraint. The outage
probability constraint requires that the secrecy rate exceeds certain threshold
with high probability. Therefore including such constraint in the design
naturally ensures the desired robustness. Unfortunately, the presence of the
probabilistic constraints makes the problem non-convex and hence difficult to
solve. In this paper, we investigate the outage probability constrained secrecy
rate maximization problem using a novel two-step approach. Under a wide range
of uncertainty models, our developed algorithms can obtain high-quality
solutions, sometimes even exact global solutions, for the robust secure
beamformer design problem. Simulation results are presented to verify the
effectiveness and robustness of the proposed algorithms
Robust Symbol Level Precoding for Overlay Cognitive Radio Networks
This paper focuses on designing robust symbol-level precoding (SLP) in the
downlink of an overlay cognitive radio (CR) network, where a primary base
station (PBS) serving primary users (PUs) and a cognitive base station (CBS)
serving cognitive users (CUs) share the same frequency band. When the PBS
shares data and perfect channel state information (CSI) with the CBS, an SLP
approach which minimizes the CR transmission power and satisfies symbol-wise
Safety Margin (SM) constraints of both PUs and CUs, is obtained in a
low-complexity quadratic formulation. Then for the case of imperfect CSI from
the PBS to CBS, we propose robust SLP schemes. First, with a norm-bounded CSI
error model to approximate uncertain channels at the PBS, we adopt the max-min
philosophy to conservatively achieve robust SLP constraints. Second, we use the
additive quantization noise model (AQNM) to describe the statistics of the
quantized PBS CSI, and we employ a stochastic constraint to formulate the
problem, where the SM constraints are converted to be deterministic. Simulation
results show that the proposed robust SLP schemes help enable PUs to mitigate
negative effect of the quantization noise and simultaneously offer CR
transmission with significant improvements in energy efficiency compared to
non-robust methods.Comment: 30 pages, 13 figures, journa
Outage-Constrained Beamforming for Two-Tier Massive MIMO Downlink with Pilot Reuse
Massive multiple-input multiple-output (MIMO) systems and small cell networks are both regarded as promising candidates to meet the exponential growth of mobile data traffic for the next generation (5G) wireless communications. Hence, a new kind of multitier networks which combine massive MIMO macro cells with a secondary tier of small cells is proposed to resolve the contradiction of large network coverage and high data rate. In such multitier networks, it is inevitable to allocate nonorthogonal uplink pilot sequences to user equipment (UE) due to the large number of users. We propose a pilot reuse scheme by exploiting the unique architecture of this networks and analyse the special mixed channel state information (CSI) yielded by the pilot reuse scheme. Based on the mixed CSI, we formulate a downlink transmit beamforming problem of minimizing the total power consumption while satisfying the quality of service (QoS) requirements with outage constraints. After decomposing the original problem into simpler subproblems, we provide an efficient algorithm to combine these subproblems and solve them iteratively for generating the beamforming vectors. Monte Carlo simulations show that the average power consumption of the proposed pilot reuse scheme and its associated beamforming algorithm is close to that of the perfect CSI case