Performance Evaluation and Enhancement in 5G Networks : A Stochastic Geometry Approach

PhDThe deployment of heterogeneous networks (HetNets), in which low power nodes (LPNs) and high power nodes (HPNs) coexist, has become a promising solution for extending coverage and increasing capacity in wireless networks. Meanwhile, several advanced technologies such as massive multi-input multi-output (MIMO), cloud radio access networks (C-RAN) and device-to-device (D2D) communications have been proposed as competent candidates for supporting the next generation (5G) network. Since single technology cannot solely achieve the envisioned 5G requirements, the e ect of integrating multiple technologies in one system is worth to be investigated. In this thesis, a thoroughly theoretical analysis is conducted to evaluate the network performance in di erent scenarios, where two or more 5G techniques are employed. First, the downlink performance of massive MIMO enabled HetNets is fully evaluated. The exact and asymptotic expressions for the probability of a user being associated with a macro cell or a small cell are presented. The analytical expressions for the spectrum e ciency (SE) and energy e ciency (EE) in the K-tier network are also derived. The analysis reveals that the implementation of massive MIMO in the macro cell can considerably improve the network performance and decrease the demands for small cells in HetNets, which simpli es the network deployment. Then, the downlink performance of a massive MIMO enabled heterogeneous C-RAN is investigated. The exact expressions for the SE and EE of the remote radio heads (RRHs) tier and a tractable approximation approach for evaluating the SE and EE of the macrocell tier are obtained. Numerical results collaborate the analysis and prove that massive MIMO with dense deployment of RRHs can signi cantly enhance the performance of heterogeneous C-RAN theoretically. Next, the uplink performance of massive MIMO enabled HetNets is exploited with interference management via derived SE and EE expressions. The numerical results show that the uplink performance in the massive MIMO macrocells can be signi cantly improved through uplink power control in the small cells, while more uplink transmissions in the macrocells have mild adverse e ect on the uplink performance of the small cells. In addition, the SE and EE of the massive MIMO macrocells with heavier load can be improved by expanding the small cell range. Lastly, the uplink performance of the D2D underlaid massive MIMO network is investigated and a novel D2D power control scheme is proposed. The average uplink achievable SE and EE expressions for the cellular and D2D are derived and results demonstrate that the proposed power control can e ciently mitigate the interference from the D2D. Moreover, the D2D scale properties are obtained, which provide the su cient conditions for achieving the anticipated SE. The results demonstrate that there exists the optimal D2D density for maximizing the area SE of D2D tier. In addition, the achievable EE of a cellular user can be comparable to that of a D2D user. Stochastic geometry is applied to model all of the systems mentioned above. Monte Carlo simulations are also developed and conducted to validate the derived expressions and the theoretical analysis

Spectral and Energy Efficiency of Uplink D2D Underlaid Massive MIMO Cellular Networks

CCBY One of key 5G scenarios is that device-to-device (D2D) and massive multiple-input multiple-output (MIMO) will be co-existed. However, interference in the uplink D2D underlaid massive MIMO cellular networks needs to be coordinated, due to the vast cellular and D2D transmissions. To this end, this paper introduces a spatially dynamic power control solution for mitigating the cellular-to-D2D and D2D-to-cellular interference. In particular, the proposed D2D power control policy is rather flexible including the special cases of no D2D links or using maximum transmit power. Under the considered power control, an analytical approach is developed to evaluate the spectral efficiency (SE) and energy efficiency (EE) in such networks. Thus, the exact expressions of SE for a cellular user or D2D transmitter are derived, which quantify the impacts of key system parameters such as massive MIMO antennas and D2D density. Moreover, the D2D scale properties are obtained, which provide the sufficient conditions for achieving the anticipated SE. Numerical results corroborate our analysis and show that the proposed power control solution can efficiently mitigate interference between the cellular and D2D tier. The results demonstrate that there exists the optimal D2D density for maximizing the area SE of D2D tier. In addition, the achievable EE of a cellular user can be comparable to that of a D2D user

Spectral and Energy Efficient D2D Communication Underlay 5G Networks: A Mixed Strategy Approach

4G is now deployed all over the world, but requirements are about to change rapidly face to the exponential growth on devices number, local service applications and spectrum scarce. To deal with that, 5G networks integrated Device To Device (D2D) communication as a key technology in its evolving architecture. From 3GPP Rel-12 to Rel-16, D2D succeeded to improve network capacity by enhancing spectrum reuse, data rates and reducing end-to-end latency. However, despite all these advantages, it implies new challenges in 5G system design as interference, spectrum and energy consumption. As a contribution, we propose in this paper a joint spectrum and energy efficient resource allocation algorithm for D2D communications. This approach maximizes the total spectrum efficiency and reduces UEs power consumption. Contrarily to most of previous studies on resource allocation problems considering only centralized and pure strategies approaches, we propose a distributed algorithm based on new mathematical game theory model as an interpretation of mixed strategy non cooperative game. We extend our previous research, by focusing on power consumption issue. Our proposed solution enhances joint SE/EE tradeoff by minimizing interferences and power consumption via a smart RB allocation. This new approach allows users to adopt more accurate strategies and maximize their utilities according to the random network behavior

Integrated cellular and device-to-device networks

textDevice-to-device (D2D) networking enables direct discovery and communication between cellular subscribers that are in proximity, thus bypassing the base stations (BSs). In principle, exploiting direct communication between nearby mobile devices will improve spectrum utilization, overall throughput, and energy consumption, while enabling new peer-to-peer and location-based applications and services. D2D-enabled broadband communication technology is also required by public safety networks that must function when cellular networks are not available. Integrating D2D into cellular networks, however, poses many challenges and risks to the long-standing cellular architecture, which is centered around the BSs. This dissertation identifies outstanding technical challenges in D2D-enabled cellular networks and addresses them with novel models and fundamental analysis. First, this dissertation develops a baseline hybrid network model consisting of both ad hoc nodes and cellular infrastructure. This model uses Poisson point processes to model the random and unpredictable locations of mobile users. It also captures key features of multicast D2D including multicast receiver heterogeneity and retransmissions while being tractable for analytical purpose. Several important multicast D2D metrics including coverage probability, mean number of covered receivers per multicast session, and multicast throughput are analytically characterized under the proposed model. Second, D2D mode selection which means that a potential D2D pair can switch between direct and cellular modes is incorporated into the hybrid network model. The extended model is applied to study spectrum sharing between cellular and D2D communications. Two spectrum sharing models, overlay and underlay, are investigated under a unified analytical framework. Analytical rate expressions are derived and applied to optimize the design of spectrum sharing. It is found that, from an overall mean-rate perspective, both overlay and underlay bring performance improvements (vs. pure cellular). Third, the single-antenna hybrid network model is extended to multi-antenna transmission to study the interplay between massive MIMO (multi-input multiple-output) and underlaid D2D networking. The spectral efficiency of such multi-antenna hybrid networks is investigated under both perfect and imperfect channel state information (CSI) assumptions. Compared to the case without D2D, there is a loss in cellular spectral efficiency due to D2D underlay. With perfect CSI, the loss can be completely overcome if the number of canceled D2D interfering signals is scaled appropriately. With imperfect CSI, in addition to pilot contamination, a new asymptotic underlay contamination effect arises. Finally, motivated by the fact that transmissions in D2D discovery are usually not or imperfectly synchronized, this dissertation studies the effect of asynchronous multicarrier transmission and proposes a tractable signal-to-interference-plus-noise ratio (SINR) model. The proposed model is used to analytically characterize system-level performance of asynchronous wireless networks. The loss from lack of synchronization is quantified, and several solutions are proposed and compared to mitigate the loss.Electrical and Computer Engineerin

Robust transmission design for multicell D2D underlaid cellular networks

This paper investigates the robust transmission design (RTD) of a multicell device-to-device (D2D) underlaid cellular network with imperfect channel state information (CSI). The bounded model is adopted to characterize the CSI impairment and the aim is to maximize the worst-case sum rate of the system. To protect cellular communications, it is assumed that the interference from all D2D transmitters to each base station (BS) is power-limited. It is first shown that the worst-case signal-to-interference-plus-noise ratio (SINR) of each D2D link can be obtained directly, while that of cellular links cannot be similarly found since the channel estimation error vectors of cellular links are coupled in the SINR expressions. To solve the nonconvex problem, the objective function of the original problem is replaced with its lower bound, and the resulted problem is decomposed into multiple semidefinite programming (SDP) subproblems, which are convex and have computationally efficient solutions. An iterative RTD algorithm is then proposed to obtain a suboptimal solution. Simulation results show that D2D communication can significantly increase the performance of the conventional cellular systems while causing tolerable interference to cellular users. In addition, the proposed RTD algorithm outperforms the conventional nonrobust transmission design greatly in terms of network spectral efficiency

Relay assisted device-to-device communication with channel uncertainty

The gains of direct communication between user equipment in a network may not be fully realised due to the separation between the user equipment and due to the fading that the channel between these user equipment experiences. In order to fully realise the gains that direct (device-to-device) communication promises, idle user equipment can be exploited to serve as relays to enforce device-to-device communication. The availability of potential relay user equipment creates a problem: a way to select the relay user equipment. Moreover, unlike infrastructure relays, user equipment are carried around by people and these users are self-interested. Thus the problem of relay selection goes beyond choosing which device to assist in relayed communication but catering for user self-interest. Another problem in wireless communication is the unavailability of perfect channel state information. This reality creates uncertainty in the channel and so in designing selection algorithms, channel uncertainty awareness needs to be a consideration. Therefore the work in this thesis considers the design of relay user equipment selection algorithms that are not only device centric but that are relay user equipment centric. Furthermore, the designed algorithms are channel uncertainty aware. Firstly, a stable matching based relay user equipment selection algorithm is put forward for underlay device-to-device communication. A channel uncertainty aware approach is proposed to cater to imperfect channel state information at the devices. The algorithm is combined with a rate based mode selection algorithm. Next, to cater to the queue state at the relay user equipment, a cross-layer selection algorithm is proposed for a twoway decode and forward relay set up. The algorithm proposed employs deterministic uncertainty constraint in the interference channel, solving the selection algorithm in a heuristic fashion. Then a cluster head selection algorithm is proposed for device-to-device group communication constrained by channel uncertainty in the interference channel. The formulated rate maximization problem is solved for deterministic and probabilistic constraint scenarios, and the problem extended to a multiple-input single-out scenario for which robust beamforming was designed. Finally, relay utility and social distance based selection algorithms are proposed for full duplex decode and forward device-to-device communication set up. A worst-case approach is proposed for a full channel uncertainty scenario. The results from computer simulations indicate that the proposed algorithms offer spectral efficiency, fairness and energy efficiency gains. The results also showed clearly the deterioration in the performance of networks when perfect channel state information is assumed