2,650 research outputs found
Physical-Layer Security with Multiuser Scheduling in Cognitive Radio Networks
In this paper, we consider a cognitive radio network that consists of one
cognitive base station (CBS) and multiple cognitive users (CUs) in the presence
of multiple eavesdroppers, where CUs transmit their data packets to CBS under a
primary user's quality of service (QoS) constraint while the eavesdroppers
attempt to intercept the cognitive transmissions from CUs to CBS. We
investigate the physical-layer security against eavesdropping attacks in the
cognitive radio network and propose the user scheduling scheme to achieve
multiuser diversity for improving the security level of cognitive transmissions
with a primary QoS constraint. Specifically, a cognitive user (CU) that
satisfies the primary QoS requirement and maximizes the achievable secrecy rate
of cognitive transmissions is scheduled to transmit its data packet. For the
comparison purpose, we also examine the traditional multiuser scheduling and
the artificial noise schemes. We analyze the achievable secrecy rate and
intercept probability of the traditional and proposed multiuser scheduling
schemes as well as the artificial noise scheme in Rayleigh fading environments.
Numerical results show that given a primary QoS constraint, the proposed
multiuser scheduling scheme generally outperforms the traditional multiuser
scheduling and the artificial noise schemes in terms of the achievable secrecy
rate and intercept probability. In addition, we derive the diversity order of
the proposed multiuser scheduling scheme through an asymptotic intercept
probability analysis and prove that the full diversity is obtained by using the
proposed multiuser scheduling.Comment: 12 pages. IEEE Transactions on Communications, 201
Performance of Cross-layer Design with Multiple Outdated Estimates in Multiuser MIMO System
By combining adaptive modulation (AM) and automatic repeat request (ARQ) protocol as well as user scheduling, the cross-layer design scheme of multiuser MIMO system with imperfect feedback is presented, and multiple outdated estimates method is proposed to improve the system performance. Based on this method and imperfect feedback information, the closed-form expressions of spectral efficiency (SE) and packet error rate (PER) of the system subject to the target PER constraint are respectively derived. With these expressions, the system performance can be effectively evaluated. To mitigate the effect of delayed feedback, the variable thresholds (VTs) are also derived by means of the maximum a posteriori method, and these VTs include the conventional fixed thresholds (FTs) as special cases. Simulation results show that the theoretical SE and PER are in good agreement with the corresponding simulation. The proposed CLD scheme with multiple estimates can obtain higher SE than the existing CLD scheme with single estimate, especially for large delay. Moreover, the CLD scheme with VTs outperforms that with conventional FTs
Resource allocation for transmit hybrid beamforming in decoupled millimeter wave multiuser-MIMO downlink
This paper presents a study on joint radio resource allocation and hybrid precoding in multicarrier massive multiple-input multiple-output communications for 5G cellular networks. In this paper, we present the resource allocation algorithm to maximize the proportional fairness (PF) spectral efficiency under the per subchannel power and the beamforming rank constraints. Two heuristic algorithms are designed. The proportional fairness hybrid beamforming algorithm provides the transmit precoder with a proportional fair spectral efficiency among users for the desired number of radio-frequency (RF) chains. Then, we transform the number of RF chains or rank constrained optimization problem into convex semidefinite programming (SDP) problem, which can be solved by standard techniques. Inspired by the formulated convex SDP problem, a low-complexity, two-step, PF-relaxed optimization algorithm has been provided for the formulated convex optimization problem. Simulation results show that the proposed suboptimal solution to the relaxed optimization problem is near-optimal for the signal-to-noise ratio SNR <= 10 dB and has a performance gap not greater than 2.33 b/s/Hz within the SNR range 0-25 dB. It also outperforms the maximum throughput and PF-based hybrid beamforming schemes for sum spectral efficiency, individual spectral efficiency, and fairness index
Exploiting Full-duplex Receivers for Achieving Secret Communications in Multiuser MISO Networks
We consider a broadcast channel, in which a multi-antenna transmitter (Alice)
sends confidential information signals to legitimate users (Bobs) in
the presence of eavesdroppers (Eves). Alice uses MIMO precoding to generate
the information signals along with her own (Tx-based) friendly jamming.
Interference at each Bob is removed by MIMO zero-forcing. This, however, leaves
a "vulnerability region" around each Bob, which can be exploited by a nearby
Eve. We address this problem by augmenting Tx-based friendly jamming (TxFJ)
with Rx-based friendly jamming (RxFJ), generated by each Bob. Specifically,
each Bob uses self-interference suppression (SIS) to transmit a friendly
jamming signal while simultaneously receiving an information signal over the
same channel. We minimize the powers allocated to the information, TxFJ, and
RxFJ signals under given guarantees on the individual secrecy rate for each
Bob. The problem is solved for the cases when the eavesdropper's channel state
information is known/unknown. Simulations show the effectiveness of the
proposed solution. Furthermore, we discuss how to schedule transmissions when
the rate requirements need to be satisfied on average rather than
instantaneously. Under special cases, a scheduling algorithm that serves only
the strongest receivers is shown to outperform the one that schedules all
receivers.Comment: IEEE Transactions on Communication
Power Allocation Schemes for Multicell Massive MIMO Systems
This paper investigates the sum-rate gains brought by power allocation
strategies in multicell massive multipleinput multiple-output systems, assuming
time-division duplex transmission. For both uplink and downlink, we derive
tractable expressions for the achievable rate with zero-forcing receivers and
precoders respectively. To avoid high complexity joint optimization across the
network, we propose a scheduling mechanism for power allocation, where in a
single time slot, only cells that do not interfere with each other adjust their
transmit powers. Based on this, corresponding transmit power allocation
strategies are derived, aimed at maximizing the sum rate per-cell. These
schemes are shown to bring considerable gains over equal power allocation for
practical antenna configurations (e.g., up to a few hundred). However, with
fixed number of users (N), these gains diminish as M turns to infinity, and
equal power allocation becomes optimal. A different conclusion is drawn for the
case where both M and N grow large together, in which case: (i) improved rates
are achieved as M grows with fixed M/N ratio, and (ii) the relative gains over
the equal power allocation diminish as M/N grows. Moreover, we also provide
applicable values of M/N under an acceptable power allocation gain threshold,
which can be used as to determine when the proposed power allocation schemes
yield appreciable gains, and when they do not. From the network point of view,
the proposed scheduling approach can achieve almost the same performance as the
joint power allocation after one scheduling round, with much reduced
complexity
A Hierarchical Rate Splitting Strategy for FDD Massive MIMO under Imperfect CSIT
In a multiuser MIMO broadcast channel, the rate performance is affected by
the multiuser interference when the Channel State Information at the
Transmitter (CSIT) is imperfect. To tackle the interference problem, a
Rate-Splitting (RS) approach has been proposed recently, which splits one
user's message into a common and a private part, and superimposes the common
message on top of the private messages. The common message is drawn from a
public codebook and should be decoded by all users. In this paper, we propose a
novel and general framework, denoted as Hierarchical Rate Splitting (HRS), that
is particularly suited to FDD massive MIMO systems. HRS simultaneously
transmits private messages intended to each user and two kinds of common
messages that can be decoded by all users and by a subset of users,
respectively. We analyse the asymptotic sum rate of HRS under imperfect CSIT. A
closed-form power allocation is derived which provides insights into the
effects of system parameters. Finally, simulation results validate the
significant sum rate gain of HRS over various baselines.Comment: Accepted paper at IEEE CAMAD 201
How much does transmit correlation affect the sum-rate scaling of MIMO Gaussian broadcast channels?
This paper considers the effect of spatial correlation between transmit antennas on the sum-rate capacity of the MIMO Gaussian broadcast channel (i.e., downlink of a cellular system). Specifically, for a system with a large number of users n, we analyze the scaling laws of the sum-rate for the dirty paper coding and for different types of beamforming transmission schemes. When the channel is i.i.d., it has been shown that for large n, the sum rate is equal to M log log n + M log P/M + o(1) where M is the number of transmit antennas, P is the average signal to noise ratio, and o(1) refers to terms that go to zero as n â â. When the channel exhibits some spatial correlation with a covariance matrix R (non-singular with tr(R) = M), we prove that the sum rate of dirty paper coding is M log log n + M log P/M + log det(R) + o(1). We further show that the sum-rate of various beamforming schemes achieves M log log n + M log P/M + M log c + o(1) where c †1 depends on the type of beamforming. We can in fact compute c for random beamforming proposed in and more generally, for random beamforming with preceding in which beams are pre-multiplied by a fixed matrix. Simulation results are presented at the end of the paper
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