236 research outputs found
Power-efficient resource allocation in NOMA virtualized wireless networks
In this paper, we address a power-efficient resource
allocation problem in virtualized wireless networks (VWNs) using
non-orthogonal multiple access (NOMA). In this set-up, the resources
of one base station (BS) are shared among different service
providers (slices), where the minimum reserved rate is considered
for each slice for guaranteeing their isolation. The formulated
resource allocation problem aiming to minimize the total transmit
power subject to the isolation constraints is non-convex and suffers
from high computational complexity. By applying complementary
geometric programming (CGP) to convert the non-convex problem
into the convex form, we develop an efficient iterative approach
with low computational complexity to solve the proposed problem.
Illustrative simulation results on the performance evaluation of
VWN using OFDMA and NOMA indicate significant performance
improvement in the VWN when NOMA is used
Dynamic resource allocation for MC-NOMA VWNs with imperfect SIC
In this work, we investigate the uplink resource allocation problem for virtualized wireless networks (VWNs) supported by multi-carrier non-orthogonal multiple access (MC-NOMA) and present a sensitivity analysis of such a system to imperfect successive interference cancellation (SIC) and various system parameters. The proposed algorithm for power and sub-carrier allocation is derived from the non-convex optimization minimizing power subject to rate and sub-carrier reservations, for which an optimal solution is NP-hard. To develop an efficient solution, we decompose the optimization into separate power and sub-carrier allocation problems and propose an iterative algorithm based on successive convex approximation and complementary geometric programming. Simulation results demonstrate that compared to orthogonal multiple access, for imperfect SIC with residual interference even up to 10%, the proposed algorithm for MC-NOMA can offer significant improvement in spectrum and power efficienc
Cooperative Multi-Bitrate Video Caching and Transcoding in Multicarrier NOMA-Assisted Heterogeneous Virtualized MEC Networks
Cooperative video caching and transcoding in mobile edge computing (MEC)
networks is a new paradigm for future wireless networks, e.g., 5G and 5G
beyond, to reduce scarce and expensive backhaul resource usage by prefetching
video files within radio access networks (RANs). Integration of this technique
with other advent technologies, such as wireless network virtualization and
multicarrier non-orthogonal multiple access (MC-NOMA), provides more flexible
video delivery opportunities, which leads to enhancements both for the
network's revenue and for the end-users' service experience. In this regard, we
propose a two-phase RAF for a parallel cooperative joint multi-bitrate video
caching and transcoding in heterogeneous virtualized MEC networks. In the cache
placement phase, we propose novel proactive delivery-aware cache placement
strategies (DACPSs) by jointly allocating physical and radio resources based on
network stochastic information to exploit flexible delivery opportunities.
Then, for the delivery phase, we propose a delivery policy based on the user
requests and network channel conditions. The optimization problems
corresponding to both phases aim to maximize the total revenue of network
slices, i.e., virtual networks. Both problems are non-convex and suffer from
high-computational complexities. For each phase, we show how the problem can be
solved efficiently. We also propose a low-complexity RAF in which the
complexity of the delivery algorithm is significantly reduced. A Delivery-aware
cache refreshment strategy (DACRS) in the delivery phase is also proposed to
tackle the dynamically changes of network stochastic information. Extensive
numerical assessments demonstrate a performance improvement of up to 30% for
our proposed DACPSs and DACRS over traditional approaches.Comment: 53 pages, 24 figure
Outage-constrained resource allocation in uplink NOMA for critical applications
In this work, we consider the resource allocation problem for uplink non-orthogonal multiple access (NOMA) networks whose users represent power-restricted but high priority devices, such as those used in sensor networks supporting health and public safety applications. Such systems require high reliability and robust resource allocation techniques are needed to ensure performance. We examine the impact on system and user performance due to residual cancellation errors resulting from imperfect successive interference cancellation (SIC) and apply the chance-constrained robust optimization approach to tackle this type of error. In particular, we derive an expression for the user outage probability as a function of SIC error variance. This result is used to formulate a robust joint resource allocation problem that minimizes user transmit power subject to rate and outage constraints of critical applications. As the proposed optimization problem is inherently non-convex and NP-hard, we apply the techniques of variable relaxation and complementary geometric programming to develop a computationally tractable two-step iterative algorithm based on successive convex approximation. Simulation results demonstrate that, even for high levels of SIC error, the proposed robust algorithm for NOMA outperforms the traditional orthogonal multiple access case in terms of user transmit power and overall system density, i.e., serving more users over fewer sub-carriers. The chance-constrained approach necessitates a power-robustness trade-off compared to non-robust NOMA but effectively enforces maximum user outage and can result in transmit power savings when users can accept a higher probability of outage
Wearable Communications in 5G: Challenges and Enabling Technologies
As wearable devices become more ingrained in our daily lives, traditional
communication networks primarily designed for human being-oriented applications
are facing tremendous challenges. The upcoming 5G wireless system aims to
support unprecedented high capacity, low latency, and massive connectivity. In
this article, we evaluate key challenges in wearable communications. A
cloud/edge communication architecture that integrates the cloud radio access
network, software defined network, device to device communications, and
cloud/edge technologies is presented. Computation offloading enabled by this
multi-layer communications architecture can offload computation-excessive and
latency-stringent applications to nearby devices through device to device
communications or to nearby edge nodes through cellular or other wireless
technologies. Critical issues faced by wearable communications such as short
battery life, limited computing capability, and stringent latency can be
greatly alleviated by this cloud/edge architecture. Together with the presented
architecture, current transmission and networking technologies, including
non-orthogonal multiple access, mobile edge computing, and energy harvesting,
can greatly enhance the performance of wearable communication in terms of
spectral efficiency, energy efficiency, latency, and connectivity.Comment: This work has been accepted by IEEE Vehicular Technology Magazin
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