195 research outputs found
A Survey of Physical Layer Security Techniques for 5G Wireless Networks and Challenges Ahead
Physical layer security which safeguards data confidentiality based on the
information-theoretic approaches has received significant research interest
recently. The key idea behind physical layer security is to utilize the
intrinsic randomness of the transmission channel to guarantee the security in
physical layer. The evolution towards 5G wireless communications poses new
challenges for physical layer security research. This paper provides a latest
survey of the physical layer security research on various promising 5G
technologies, including physical layer security coding, massive multiple-input
multiple-output, millimeter wave communications, heterogeneous networks,
non-orthogonal multiple access, full duplex technology, etc. Technical
challenges which remain unresolved at the time of writing are summarized and
the future trends of physical layer security in 5G and beyond are discussed.Comment: To appear in IEEE Journal on Selected Areas in Communication
Joint Power Allocation and User Association Optimization for Massive MIMO Systems
This paper investigates the joint power allocation and user association
problem in multi-cell Massive MIMO (multiple-input multiple-output) downlink
(DL) systems. The target is to minimize the total transmit power consumption
when each user is served by an optimized subset of the base stations (BSs),
using non-coherent joint transmission. We first derive a lower bound on the
ergodic spectral efficiency (SE), which is applicable for any channel
distribution and precoding scheme. Closed-form expressions are obtained for
Rayleigh fading channels with either maximum ratio transmission (MRT) or zero
forcing (ZF) precoding. From these bounds, we further formulate the DL power
minimization problems with fixed SE constraints for the users. These problems
are proved to be solvable as linear programs, giving the optimal power
allocation and BS-user association with low complexity. Furthermore, we
formulate a max-min fairness problem which maximizes the worst SE among the
users, and we show that it can be solved as a quasi-linear program. Simulations
manifest that the proposed methods provide good SE for the users using less
transmit power than in small-scale systems and the optimal user association can
effectively balance the load between BSs when needed. Even though our framework
allows the joint transmission from multiple BSs, there is an overwhelming
probability that only one BS is associated with each user at the optimal
solution.Comment: 16 pages, 12 figures, Accepted by IEEE Trans. Wireless Commu
Recommended from our members
QoS-Constraints and Pilot-Contamination in the Uplink of Non-cooperative Cellular Massive-MIMO
This paper investigates the statistical-queueing con-straints and pilot contamination phenomenon in random or ir-regular cellular massive multiple-input-multiple-output (MIMO) system where base stations are Poisson distributed. Specifically, analytical expressions for the asymptotic signal-to-interference-ratio (SIR) coverage, rate-coverage and effective capacity under quality of service (QoS) statistical-exponent constraint are pro-vided for uplink transmission when each base station deploys a large number of antennas. We show that the QoS constrained capacity is in proportional to the path-loss exponent and inversely proportional to the pilot reusing probability which in turn is a function of cell load.
Our simulation results prove that, pilot reuse impairments can be alleviated by employing a cellular frequency-reuse scheme. For example, with unity frequency reuse factor, we see that, 40% of the total users have SIR above −10.5dB , whereas, with frequency reuse factor of Ω = 7, the same fraction of users has SIR above 20.5dB. However, this can reduce the effective bandwidth of overall system, e.g., for 15% level, the rate drop is almost 10Mbps due to using reuse factor of Ω = 7
Energy-Efficient NOMA Enabled Heterogeneous Cloud Radio Access Networks
Heterogeneous cloud radio access networks (H-CRANs) are envisioned to be
promising in the fifth generation (5G) wireless networks. H-CRANs enable users
to enjoy diverse services with high energy efficiency, high spectral
efficiency, and low-cost operation, which are achieved by using cloud computing
and virtualization techniques. However, H-CRANs face many technical challenges
due to massive user connectivity, increasingly severe spectrum scarcity and
energy-constrained devices. These challenges may significantly decrease the
quality of service of users if not properly tackled. Non-orthogonal multiple
access (NOMA) schemes exploit non-orthogonal resources to provide services for
multiple users and are receiving increasing attention for their potential of
improving spectral and energy efficiency in 5G networks. In this article a
framework for energy-efficient NOMA H-CRANs is presented. The enabling
technologies for NOMA H-CRANs are surveyed. Challenges to implement these
technologies and open issues are discussed. This article also presents the
performance evaluation on energy efficiency of H-CRANs with NOMA.Comment: This work has been accepted by IEEE Network. Pages 18, Figure
Energy efficiency and interference management in long term evolution-advanced networks.
Doctoral Degree. University of KwaZulu-Natal, Durban.Cellular networks are continuously undergoing fast extraordinary evolution to overcome
technological challenges. The fourth generation (4G) or Long Term Evolution-Advanced
(LTE-Advanced) networks offer improvements in performance through increase in network density,
while allowing self-organisation and self-healing. The LTE-Advanced architecture is heterogeneous,
consisting of different radio access technologies (RATs), such as macrocell, smallcells, cooperative
relay nodes (RNs), having various capabilities, and coexisting in the same geographical coverage
area. These network improvements come with different challenges that affect users’ quality of
service (QoS) and network performance. These challenges include; interference management, high
energy consumption and poor coverage of marginal users. Hence, developing mitigation schemes for
these identified challenges is the focus of this thesis.
The exponential growth of mobile broadband data usage and poor networks’ performance along
the cell edges, result in a large increase of the energy consumption for both base stations (BSs) and
users. This due to improper RN placement or deployment that creates severe inter-cell and intracell
interferences in the networks. It is therefore, necessary to investigate appropriate RN placement
techniques which offer efficient coverage extension while reducing energy consumption and mitigating
interference in LTE-Advanced femtocell networks. This work proposes energy efficient and optimal
RN placement (EEORNP) algorithm based on greedy algorithm to assure improved and effective
coverage extension. The performance of the proposed algorithm is investigated in terms of coverage
percentage and number of RN needed to cover marginalised users and found to outperform other RN
placement schemes.
Transceiver design has gained importance as one of the effective tools of interference
management. Centralised transceiver design techniques have been used to improve network
performance for LTE-Advanced networks in terms of mean square error (MSE), bit error rate (BER)
and sum-rate. The centralised transceiver design techniques are not effective and computationally
feasible for distributed cooperative heterogeneous networks, the systems considered in this thesis.
This work proposes decentralised transceivers design based on the least-square (LS) and minimum MSE (MMSE) pilot-aided channel estimations for interference management in uplink
LTE-Advanced femtocell networks. The decentralised transceiver algorithms are designed for the
femtocells, the macrocell user equipments (MUEs), RNs and the cell edge macrocell UEs (CUEs) in
the half-duplex cooperative relaying systems. The BER performances of the proposed algorithms
with the effect of channel estimation are investigated.
Finally, the EE optimisation is investigated in half-duplex multi-user multiple-input
multiple-output (MU-MIMO) relay systems. The EE optimisation is divided into sub-optimal EE
problems due to the distributed architecture of the MU-MIMO relay systems. The decentralised
approach is employed to design the transceivers such as MUEs, CUEs, RN and femtocells for the
different sub-optimal EE problems. The EE objective functions are formulated as convex
optimisation problems subject to the QoS and transmit powers constraints in case of perfect channel
state information (CSI). The non-convexity of the formulated EE optimisation problems is
surmounted by introducing the EE parameter substractive function into each proposed algorithms.
These EE parameters are updated using the Dinkelbach’s algorithm. The EE optimisation of the
proposed algorithms is achieved after finding the optimal transceivers where the unknown
interference terms in the transmit signals are designed with the zero-forcing (ZF) assumption and
estimation errors are added to improve the EE performances. With the aid of simulation results, the
performance of the proposed decentralised schemes are derived in terms of average EE evaluation
and found to be better than existing algorithms
Downlink Training in Cell-Free Massive MIMO: A Blessing in Disguise
Cell-free Massive MIMO (multiple-input multiple-output) refers to a
distributed Massive MIMO system where all the access points (APs) cooperate to
coherently serve all the user equipments (UEs), suppress inter-cell
interference and mitigate the multiuser interference. Recent works demonstrated
that, unlike co-located Massive MIMO, the \textit{channel hardening} is, in
general, less pronounced in cell-free Massive MIMO, thus there is much to
benefit from estimating the downlink channel. In this study, we investigate the
gain introduced by the downlink beamforming training, extending the previously
proposed analysis to non-orthogonal uplink and downlink pilots. Assuming
single-antenna APs, conjugate beamforming and independent Rayleigh fading
channel, we derive a closed-form expression for the per-user achievable
downlink rate that addresses channel estimation errors and pilot contamination
both at the AP and UE side. The performance evaluation includes max-min
fairness power control, greedy pilot assignment methods, and a comparison
between achievable rates obtained from different capacity-bounding techniques.
Numerical results show that downlink beamforming training, although increases
pilot overhead and introduces additional pilot contamination, improves
significantly the achievable downlink rate. Even for large number of APs, it is
not fully efficient for the UE relying on the statistical channel state
information for data decoding.Comment: Published in IEEE Transactions on Wireless Communications on August
14, 2019. {\copyright} 2019 IEEE. Personal use of this material is permitted.
Permission from IEEE must be obtained for all other use
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