Supporting ever increasing number of mobile users with data-hungry applications, running on battery limited devices, is a daunting challenge for telecommunications community. Underlay device-to-device (D2D) communication, which allows physically proximate mobile users to directly communicate with each other by reusing the spec
trum, without going through the base station, holds promise to help us tackle this challenge. In a cellular network, underlay D2D communication offers opportunities for spectrum reuse and spatial diversity which may lead to enhanced coverage, higher
throughput, and robust communication in the network. Further, for applications such
as weather forecasting and live streaming, which may require the same chunks of data distributed to geographically proximate users, D2D multicasting may provide better utilization of network resources compared to D2D unicast or Base Station (BS) based
multicast, such as LTE eMBMS. However, extensive deployment of underlay D2D mul
ticast in a network may cause severe co-channel interference due to spectrum reuse and
rapid battery depletion of the multicasting D2D nodes as they may have to expend
more power to fight co-channel interference and to relay data. Therefore, in this thesis,
we focus on some of the challenges in supporting D2D multicast communication in un
derlay cellular networks, propose novel approaches to address these challenges without
compromising on the promise of D2D multicast in cellular networks, and evaluate their performances.
In the first part of the thesis, we study the resource allocation schemes where
multiple D2D multicast groups may share cellular users’ uplink channels. We formu
late an optimization problem that maximizes the achievable system throughput while fulfilling the maximum power constraint of every cellular user and multicast group
transmitter, and ensuring a certain level of quality of service (QoS) to every cellular
user and D2D multicast group. The formulated optimization problem is an instance
of mixed integer non-linear programming (MINLP) problem, which is computationally
intractable, in general. Therefore, to find a feasible solution, we propose a pragmatic
two-step process of channel allocation and power allocation. In the first-step, we pro
pose a channel sharing algorithm, which determines the subset of multicast groups that
may share a channel. Then, we propose a power allocation algorithm that maximizes
the system throughput, while satisfying transmit power and interference constraints.
We demonstrate impact of the QoS requirements of CUs and the maximum available
transmission power on achievable system throughput. Further, we also explore the
problem of sum rate maximization over general fading environments. In particular, we
provide an exact calculation of outage probability experienced by a D2D receiver in a
multicast group and a scheme to optimally share channels among D2D MGs and CUs by minimizing these probabilities.
In the second part of the thesis, we address the problem of mutual interference minimization between cellular users and D2D multicast groups by adopting a realistic and pragmatic approach to effectively reduce the co-channel interference of cellular
transmission on D2D multicast reception. We consider the cellular users as the primary users in a cell, having exclusion zones around them, where no receiver of any
multicast group can exist. We use a stochastic geometry based approach to model
this scenario and formulate the corresponding network sum throughput maximization
problem. Specifically, we model the locations of cellular users and D2D multicast
groups receivers with two different spatial distributions, namely homogeneous Poisson Point Process (PPP), and Poisson Hole Process (PHP), respectively. The D2D
multicast groups are enabled only when their receivers are outside cellular users’ exclusion regions. In this setting, we formulate a network sum throughput maximization
problem in terms of joint multicast group channel and power allocation problem with constraints on the maximum power of D2D transmitters and acceptable quality of service of cellular users and multicast group receivers. We prove that the channel
allocation problem has computational complexity at least exponential in both, the number of cellular users and the number of multicast groups. However, after numerically analyzing the nature of the optimal solution in a wide variety of scenarios, we
observe that though theoretically any number of multicast groups can be assigned to any cellular channel, the optimal performance is invariably achieved when small and almost equal number of multicast groups are assigned to all channels. Based on this
observation, we propose schemes that achieve almost optimal performance with reducing computational complexity in the number of multicast groups. We also provide a novel scheme to reduce the complexity with respect to the number of cellular channels.
We further compare the performance of the proposed schemes with the performance of
the optimal scheme with respect to variation of different system parameters and show
that the proposed schemes achieve almost optimal performance in computationally
efficient manner.
In the third part of the thesis, we introduce an approach based on stochastic
geometry to derive the relation between average sum-rate and energy consumption. In
particular, we explore spectral efficiency (SE) and energy efficiency (EE) trade-off for
this problem by formulating the EE maximization problem with constraint on SE and
maximum available transmission power. The formulated problem is non-convex, and is
solved using a proposed heuristic gradient power allocation algorithm. It is shown that
energy efficiency has a non-trivial behavior due to complex interplay among various
system parameters, such as available power, spectral requirements, and D2D multicast
groups density. There is an optimal value of SE that can be supported, which results in
the corresponding maximal value of EE for each value of multicast group transmitter power. Concluding, in this work, we highlight various aspects of D2D multicast in underlay cellular networks through analytical and numerical frameworks, and provide insights
into the practical system design.
Supporting ever increasing number of mobile users with data-hungry applications,
running on battery limited devices, is a daunting challenge for telecommunications
community. Underlay device-to-device (D2D) communication, which allows physically
proximate mobile users to directly communicate with each other by reusing the spec
trum, without going through the base station, holds promise to help us tackle this
challenge. In a cellular network, underlay D2D communication offers opportunities
for spectrum reuse and spatial diversity which may lead to enhanced coverage, higher
throughput, and robust communication in the network. Further, for applications such
as weather forecasting and live streaming, which may require the same chunks of data
distributed to geographically proximate users, D2D multicasting may provide better
utilization of network resources compared to D2D unicast or Base Station (BS) based
multicast, such as LTE eMBMS. However, extensive deployment of underlay D2D mul
ticast in a network may cause severe co-channel interference due to spectrum reuse and
rapid battery depletion of the multicasting D2D nodes as they may have to expend
more power to fight co-channel interference and to relay data. Therefore, in this thesis,
we focus on some of the challenges in supporting D2D multicast communication in un
derlay cellular networks, propose novel approaches to address these challenges without
compromising on the promise of D2D multicast in cellular networks, and evaluate their
performances.
In the first part of the thesis, we study the resource allocation schemes where
multiple D2D multicast groups may share cellular users’ uplink channels. We formu
late an optimization problem that maximizes the achievable system throughput while
fulfilling the maximum power constraint of every cellular user and multicast group
transmitter, and ensuring a certain level of quality of service (QoS) to every cellular
user and D2D multicast group. The formulated optimization problem is an instance
of mixed integer non-linear programming (MINLP) problem, which is computationally
intractable, in general. Therefore, to find a feasible solution, we propose a pragmatic
two-step process of channel allocation and power allocation. In the first-step, we pro
pose a channel sharing algorithm, which determines the subset of multicast groups that
may share a channel. Then, we propose a power allocation algorithm that maximizes
the system throughput, while satisfying transmit power and interference constraints.
We demonstrate impact of the QoS requirements of CUs and the maximum available
transmission power on achievable system throughput. Further, we also explore the
problem of sum rate maximization over general fading environments. In particular, we
provide an exact calculation of outage probability experienced by a D2D receiver in a
multicast group and a scheme to optimally share channels among D2D MGs and CUs
by minimizing these probabilities.
In the second part of the thesis, we address the problem of mutual interference
minimization between cellular users and D2D multicast groups by adopting a realistic
and pragmatic approach to effectively reduce the co-channel interference of cellular
transmission on D2D multicast reception. We consider the cellular users as the pri
mary users in a cell, having exclusion zones around them, where no receiver of any
multicast group can exist. We use a stochastic geometry based approach to model
this scenario and formulate the corresponding network sum throughput maximization
problem. Specifically, we model the locations of cellular users and D2D multicast
groups receivers with two different spatial distributions, namely homogeneous Pois
son Point Process (PPP), and Poisson Hole Process (PHP), respectively. The D2D
multicast groups are enabled only when their receivers are outside cellular users’ ex
clusion regions. In this setting, we formulate a network sum throughput maximization
problem in terms of joint multicast group channel and power allocation problem with
constraints on the maximum power of D2D transmitters and acceptable quality of
service of cellular users and multicast group receivers. We prove that the channel
allocation problem has computational complexity at least exponential in both, the
number of cellular users and the number of multicast groups. However, after numer
ically analyzing the nature of the optimal solution in a wide variety of scenarios, we
observe that though theoretically any number of multicast groups can be assigned to
any cellular channel, the optimal performance is invariably achieved when small and
almost equal number of multicast groups are assigned to all channels. Based on this
observation, we propose schemes that achieve almost optimal performance with reduc
ing computational complexity in the number of multicast groups. We also provide a
novel scheme to reduce the complexity with respect to the number of cellular channels.
We further compare the performance of the proposed schemes with the performance of
the optimal scheme with respect to variation of different system parameters and show
that the proposed schemes achieve almost optimal performance in computationally
efficient manner.
In the third part of the thesis, we introduce an approach based on stochastic
geometry to derive the relation between average sum-rate and energy consumption. In
particular, we explore spectral efficiency (SE) and energy efficiency (EE) trade-off for
this problem by formulating the EE maximization problem with constraint on SE and
maximum available transmission power. The formulated problem is non-convex, and is
solved using a proposed heuristic gradient power allocation algorithm. It is shown that
energy efficiency has a non-trivial behavior due to complex interplay among various
system parameters, such as available power, spectral requirements, and D2D multicast
groups density. There is an optimal value of SE that can be supported, which results in
the corresponding maximal value of EE for each value of multicast group transmitter
power.
Concluding, in this work, we highlight various aspects of D2D multicast in underlay
cellular networks through analytical and numerical frameworks, and provide insights
into the practical system design.
