65,968 research outputs found
UL-DL duality for cell-free massive MIMO with per-AP power and information constraints
We derive a novel uplink-downlink duality principle for optimal joint
precoding design under per-transmitter power and information constraints in
fading channels. The information constraints model limited sharing of channel
state information and data bearing signals across the transmitters. The main
application is to cell-free networks, where each access point (AP) must
typically satisfy an individual power constraint and form its transmit signal
using limited cooperation capabilities. Our duality principle applies to
ergodic achievable rates given by the popular hardening bound, and it can be
interpreted as a nontrivial generalization of a previous result by Yu and Lan
for deterministic channels. This generalization allows us to study involved
information constraints going beyond the simple case of cluster-wise
centralized precoding covered by previous techniques. Specifically, we show
that the optimal joint precoders are, in general, given by an extension of the
recently developed team minimum mean-square error method. As a particular yet
practical example, we then solve the problem of optimal local precoding design
in user-centric cell-free massive MIMO networks subject to per-AP power
constraints
On the Benefit of Information Centric Networks for Traffic Engineering
Current Internet performs traffic engineering (TE) by estimating traffic
matrices on a regular schedule, and allocating flows based upon weights
computed from these matrices. This means the allocation is based upon a guess
of the traffic in the network based on its history. Information-Centric
Networks on the other hand provide a finer-grained description of the traffic:
a content between a client and a server is uniquely identified by its name, and
the network can therefore learn the size of different content items, and
perform traffic engineering and resource allocation accordingly. We claim that
Information-Centric Networks can therefore provide a better handle to perform
traffic engineering, resulting in significant performance gain.
We present a mechanism to perform such resource allocation. We see that our
traffic engineering method only requires knowledge of the flow size (which, in
ICN, can be learned from previous data transfers) and outperforms a min-MLU
allocation in terms of response time. We also see that our method identifies
the traffic allocation patterns similar to that of min-MLU without having
access to the traffic matrix ahead of time. We show a very significant gain in
response time where min MLU is almost 50% slower than our ICN-based TE method
Cooperative Caching and Transmission Design in Cluster-Centric Small Cell Networks
Wireless content caching in small cell networks (SCNs) has recently been
considered as an efficient way to reduce the traffic and the energy consumption
of the backhaul in emerging heterogeneous cellular networks (HetNets). In this
paper, we consider a cluster-centric SCN with combined design of cooperative
caching and transmission policy. Small base stations (SBSs) are grouped into
disjoint clusters, in which in-cluster cache space is utilized as an entity. We
propose a combined caching scheme where part of the available cache space is
reserved for caching the most popular content in every SBS, while the remaining
is used for cooperatively caching different partitions of the less popular
content in different SBSs, as a means to increase local content diversity.
Depending on the availability and placement of the requested content,
coordinated multipoint (CoMP) technique with either joint transmission (JT) or
parallel transmission (PT) is used to deliver content to the served user. Using
Poisson point process (PPP) for the SBS location distribution and a hexagonal
grid model for the clusters, we provide analytical results on the successful
content delivery probability of both transmission schemes for a user located at
the cluster center. Our analysis shows an inherent tradeoff between
transmission diversity and content diversity in our combined
caching-transmission design. We also study optimal cache space assignment for
two objective functions: maximization of the cache service performance and the
energy efficiency. Simulation results show that the proposed scheme achieves
performance gain by leveraging cache-level and signal-level cooperation and
adapting to the network environment and user QoS requirements.Comment: 13 pages, 10 figures, submitted for possible journal publicatio
Backhaul-aware Robust 3D Drone Placement in 5G+ Wireless Networks
Using drones as flying base stations is a promising approach to enhance the
network coverage and area capacity by moving supply towards demand when
required. However deployment of such base stations can face some restrictions
that need to be considered. One of the limitations in drone base stations
(drone-BSs) deployment is the availability of reliable wireless backhaul link.
This paper investigates how different types of wireless backhaul offering
various data rates would affect the number of served users. Two approaches,
namely, network-centric and user-centric, are introduced and the optimal 3D
backhaul-aware placement of a drone-BS is found for each approach. To this end,
the total number of served users and sum-rates are maximized in the
network-centric and user-centric frameworks, respectively. Moreover, as it is
preferred to decrease drone-BS movements to save more on battery and increase
flight time and to reduce the channel variations, the robustness of the network
is examined as how sensitive it is with respect to the users displacements.Comment: in Proc. IEEE ICC2017 Workshops, FlexNets201
- …