Interference-Based Decode and Forward Scheme Using Relay Nodes in Heterogeneous Networks

Heterogeneous Networks (HetNets) have gained the attraction of the communication industry recently, due to their promising ability to enhance the performance of future broadband Fifth Generation (5G) networks and are integral parts of 5G systems. They can be viewed in multi-dimensional space where, each slice represents a unique tier that has its own Base Station (BS)s and User Equipment (UE)s. Different tiers cooperate with each other for their mutual benefit. Data can be interactively exchanged among the tiers, and UEs have the flexibility to switch between the tiers. The cells in such a heterogeneous cellular networks have variable sizes, shapes, and coverage regions. However, in HetNets with ultra dense BSs, the distance between them gets very small and, they suffer from very high levels of mutual interference. To improve the performance of HetNets, we have done multiple contributions in this dissertation. First, we have developed analytical derivations for optimizing pilot sequence length which is a very crucial factor in acquiring the Channel State Information (CSI) and the channel estimation process in general. Poisson Point Process (PPP) has been widely used to allocate BSs among various tiers so far. However, BS locations obtained using PPP approach may not be optimum to reduce interference. Therefore, in this dissertation, BSs locations are optimized to reduce the interference and improve the coverage and received signal power. Also, we have derived expressions for static UEs coverage probability and network energy efficiency in HetNets. A proper UE association algorithm for HetNets is a great challenge. The classic max-Signal to Interference and Noise Ratio (SINR) or max-received signal strength (RSS) user association algorithms are inappropriate solutions for HetNets as UEs in this context will tend to connect to the Macro BS, which is the one with the highest signal power. A severe load imbalance and significant inefficiency arises and impacts the performance. The aforementioned algorithms tend to associate UEs to BSs with the best received signal power or signal quality. In HetNets, usually Macro BSs are the ones transmitting the strongest signals; hence most UEs tend to associate with the Macro BS leaving Micro BSs with less load. Also, the conventional max-SINR and max-RSS algorithms do not provide adequate results in multi-tier systems. We suggest two centralized algorithms, LSTD and RTLB, for an even UE association to provide fair load distribution. However RTLB outperforms LSTD in real time scenarios as it easily and quickly adapts to rapid network changes. Furthermore, we consider the mobility of nodes. We derive coverage probability for moving UEs considering both handover and no handover scenarios. Proposed algorithms are fast enough to associate the moving users to different Micro and Macro BSs appropriately in real time. Our algorithms are proved to be feasible and provide a path towards attainable future communication systems.

The link performance between base station (BS) and user equipment (UE) in long term evolution-advanced (LTE-A) system is already quite close to the Shannon limits and from a pure link-budget perspective, the highest data rates supported by LTE-A require a relatively high signal-to-noise ratio. In later releases of LTE-A, various tools such as relaying, enhancing the support for low-power BSs and improving the link budget are included. This paper studies the relay stations (RSs) for LTE-A downlink physical layer. Multi-input multi-output amplify-and-forward RS is used to enhance the received signal of UEs at cell edge. This paper proposes RSs with orthogonal space–time block codes (OSTBC) transmission for LTE-A system. The received signals for different UEs scenarios are mathematically derived and analyzed. The symbol error rate performance of proposed LTE-A system is illustrated for the scenarios of UEs. Results show that the proposed LTE-A system based RSs with OSTBC transmission improve link performance and achieve higher diversity gains.

This paper presents an adaptive amplify-and-forward (AF)-type relaying method appropriate for the cellular downlink. The proposed method adaptively selects active relay stations (RSs) based on the path loss between each set of user equipment (UE) and the base station (BS) and that between each RS in order to avoid unnecessary enhancement of inter-cell interference and bandwidth reduction due to transmission relay. Furthermore, to enhance the spectrum efficiency when relaying, the frequency used for the relay transmission from the RS to the cell-edge user is reused for the direct transmission from the BS to the cell-center user. Based on computer simulation, the system-level average throughput and cell-edge user throughput of the proposed method are compared to those for a case using no relaying and a conventional repeater. The simulation results show the effectiveness of the proposed method.

Integrated access and backhaul (IAB) network consists of base station (BS), relay nodes (RNs), and user-equipments (UEs), where BS and RNs exchange UE data via wireless in-band backhaul while sharing the same frequency-time resources with access links. In this paper, a flexible time-division-duplex (TDD)-based IAB network is considered where RNs and BS are assigned to distinct uplink (UL) or downlink (DL) transmission modes to mitigate conventional half-duplex (HD) loss at RNs. An iterative beamformer design is proposed to manage the resulting cross-channel interference and to allocate wireless backhaul and access resources jointly over two consecutive data delivery intervals required for communications between the BS and UEs through HD RNs. Dynamic traffic behavior is handled via weighted queue minimization objective, and user-specific UL/DL queues are also introduced at RNs to guarantee reliable end-to-end data delivery. Bi-directional forward-backward training via spatially precoded over-the-air pilot signaling is employed to allow decentralized beamformer design across all the nodes. A novel user allocation method is proposed to assign UEs to BS or RNs based only on long-term channel statistics and some practical IAB limitations. The numerical examples illustrate the superior system performance of the considered flexible IAB in comparison to the conventional HD relaying system.

The use of small cell deployments in heterogeneous network (HetNet) environments is expected to be a key feature of 4G networks and beyond, and essential for providing higher user throughput and cell-edge coverage. However, due to different coverage sizes of macro and pico base stations (BSs), such a paradigm shift introduces additional requirements and challenges in dense networks. Among these challenges is the handover performance of user equipment (UEs), which will be impacted especially when high velocity UEs traverse picocells. In this paper, we propose a coordination-based and context-aware mobility management (MM) procedure for small cell networks using tools from reinforcement learning. Here, macro and pico BSs jointly learn their long-term traffic loads and optimal cell range expansion, and schedule their UEs based on their velocities and historical rates (exchanged among tiers). The proposed approach is shown to not only outperform the classical MM in terms of UE throughput, but also to enable better fairness. In average, a gain of up to 80% is achieved for UE throughput, while the handover failure probability is reduced up to a factor of three by the proposed learning based MM approaches.

Interference alignment (IA) in heterogeneous networks (HetNet) is a promising technology that can achieve a significant increase of network capacity. However, there are some issues on IA in HetNet. One of them is that each pico base station (BS) requires a large number of transmit antennas, because it tries to align all inter-pico interference. In actual environments, the strength of inter-pico interference varies depending on the distance between pico cells, i.e., inter-pico interference from the remote pico cell is much smaller than that from the close one, so that aligning all interference is not necessarily the best. In addition, the residual interference from macro BS that is not eliminated by IA may decrease the capacity. In this paper, we propose 1) to reduce the required number of transmit antennas at pico BS by clustering pico cells based on the strength of inter-pico interference and 2) to apply combined weight, that comprises ZF (zero forcing) weight and MMSE (minimum mean square error) weight, to pico user equipment (UE) so as to mitigate the residual interference that is not eliminated perfectly by IA. Simulation results show that by applying combined weight to pico UEs, the capacity increases compared to the case of applying only ZF weight, and that the average rate per pico cell normalized by the required number of transmit antennas at each pico BS, that is, the rate per transmit antenna can be increased with pico cell clustering, which indicates that each pico BS can utilize its transmit antennas more efficiently.

This paper studies the impact of the base station (BS) idle mode capability (IMC) on the network performance of multi-tier and dense heterogeneous cellular networks (HCNs). Different from most existing works that investigated network scenarios with an infinite number of user equipments (UEs), we consider a more practical setup with a finite number of UEs in our analysis. More specifically, we derive the probability of which BS tier a typical UE should associate to and the expression of the activated BS density in each tier. Based on such results, analytical expressions for the coverage probability and the area spectral efficiency (ASE) in each tier are also obtained. The impact of the IMC on the performance of all BS tiers is shown to be significant. In particular, there will be a surplus of BSs when the BS density in each tier exceeds the UE density, and the overall coverage probability as well as the ASE continuously increase when the BS IMC is applied. Such finding is distinctively different from that in existing work. Thus, our result sheds new light on the design and deployment of the future 5G HCNs.

A K-tier heterogeneous downlink millimeter wave (mmWave) cellular network with user-centric small cell deployments is studied in this paper. In particular, we consider a heterogeneous network model with user equipments (UEs) being deployed according to a Poisson Cluster Process (PCP), i.e., Thomas cluster process, where the UEs are clustered around the base stations (BSs) and the distances between UEs and the BS are modeled as Gaussian distributed. In addition, distinguishing features of mmWave communications including directional beamforming and a sophisticated path loss model incorporating both line-of-sight (LOS) and non-line-of-sight (NLOS) transmissions, are taken into account. In this paper, the complementary cumulative distribution function (CCDF) and probability density function (PDF) of the path loss are provided. Also, using tools from stochastic geometry, we derive a general expression of the signal-to-interference-plus-noise ratio (SINR) coverage probability. Our results demonstrate that coverage probability can be improved by decreasing the size of UE clusters around BSs, and interference has noticeable influence on the coverage performance of our model.

For conventional multiple-input and multiple-output (MIMO) selective decode-and-forward (S-DF) relaying network, without global channel knowledge, base station (BS) normally allocates its transmission power for the channel links between itself and its served users. In this case, if the received signal power at relay station (RS) is larger enough, RS will help BS decode and forward the messages. However, such strategy may lose system optimality if BS has the location information of RS. Motivated by this, in this paper, a RS-oriented BS power allocation algorithm for MIMO S-DF relaying is proposed to enhance the system performance. Specifically, BS firstly allocates its transmission power to help as much as data streams to be correctly decoded at RS. Then, if there is still some power left, BS will allocate the residual power for its direct channel links to the users to further increase the system performance. Computer simulations are carried out to examine the proposed scheme in terms of sumrate and bit-error-rate. It is shown that the proposed scheme outperforms the conventional schemes, especially when the RS is placed in the middle of BS and the users.

In this paper, we present a novel cell outage management (COM) framework for heterogeneous networks with split control and data planes—a candidate architecture for meeting future capacity, quality-of-service, and energy efficiency demands. In such an architecture, the control and data functionalities are not necessarily handled by the same node. The control base stations (BSs) manage the transmission of control information and user equipment (UE) mobility, whereas the data BSs handle UE data. An implication of this split architecture is that an outage to a BS in one plane has to be compensated by other BSs in the same plane. Our COM framework addresses this challenge by incorporating two distinct cell outage detection (COD) algorithms to cope with the idiosyncrasies of both data and control planes. The COD algorithm for control cells leverages the relatively larger number of UEs in the control cell to gather large-scale minimization-of-drive-test report data and detects an outage by applying machine learning and anomaly detection techniques. To improve outage detection accuracy, we also investigate and compare the performance of two anomaly-detecting algorithms, i.e., $k$ -nearest-neighbor- and local-outlier-factor-based anomaly detectors, within the control COD. On the other hand, for data cell COD, we propose a heuristic Grey-prediction-based approach, which can work with the small number of UE in the data cell, by exploiting the fact that the control BS manages UE-data BS connectivity and by receiving a periodic update of the received signal reference power statistic between the UEs and data BSs in its coverage. The detection accuracy of the heuristic data COD algorithm is further improved by exploiting the Fourier series of the residual error that is inherent to a Grey prediction model. Our COM framework integrates these two COD algorithms with a cell outage compensation (COC) algorithm that can be applied to both planes. Our COC solution utilizes an actor-critic-based reinforcement learning algorithm, which optimizes the capacity and coverage of the identified outage zone in a plane, by adjusting the antenna gain and transmission power of the surrounding BSs in that plane. The simulation results show that the proposed framework can detect both data and control cell outage and compensate for the detected outage in a reliable manner.

In Heterogeneous networks (HetNets), the power difference between macro base stations (MBSs) and small base stations (SBSs) causes severe load unbalance. Therefore, cell range expansion (CRE) is proposed as an effective method to extend the coverage of SBSs and achieve balanced utilization of BSs. However, the downlink (DL) quality for offloaded user equipment (UE) cannot be guaranteed. In this paper, a traffic-aware user association scheme is proposed in HetNets. Distinct association biases are applied to different UEs according to their requirements. System performance of the proposed scheme is analyzed using the tool of stochastic geometry. The results show that the proposed scheme can improve DL throughput by enhancing the rate coverage of UEs, meanwhile signal-to-interference-plus-noise ratio (SINR) requirement with low data rate demand UEs is ensured. Moreover, the optimal association bias, which maximizes DL throughput, can be derived through particle swarm optimization (PSO), and it changes with different densities of BSs and UEs.

User association is a crucial factor that affects the performance of wireless networks. In current cellular networks, user association is typically coupled, which means an user equipment (UE) must associate with the same base station (BS) in uplink (UL) and downlink (DL). For single-tier wireless networks, such mechanism is simple and effective. However, in heterogeneous ultra-dense networks (UDNs), there are distinct differences in transmission power, data traffic and channel quality etc., for which coupled association could restrict the performance of system. To cope with it, the concept of decoupled UL-DL (DUDe) association has been introduced recently, which enables a UE to associate with different BSs in UL and DL. In this paper, we investigate decoupled UL-DL user association in UDNs. Considering the existence of asymmetric information (i.e., channel gains and intercell interferences), which can be seen as the private information for UE, we propose a contract-theoretic user association approach. Particularly, we model the decoupled association process as a monopoly labor market, where BSs act as employers and offer contracts to employees (i.e., UEs). The contract items cover the available associated bandwidths, transmitted powers and corresponding prices. Then BS broadcasts these drafted contract information, and UE selects to sign the optimal contract by considering her own demands. Numerical results show significant superiorities of DUDe than coupled UL-DL association in perspective of nodes utilities and social surplus, and compared with the existing user association methods, contract-theoretic approach shows a certain improvement in performance.

Low-power base stations (BSs), such as pico BSs, femto BSs, and relay nodes, are introduced to the heterogeneous cellular networks to enhance coverage and improve system capacity. Compare with macro BS, low-power BS has much lower transmission power, smaller physical size and lower cost. Deploying low-power BSs within the coverage of macro BSs is considered as a cost-efficient way to meet the sharp increase of wireless applications, leading to a new radio network planning paradigm for the next generation cellular networks. In this paper, we study the minimum cost cell planning problem in such heterogeneous networks, where planning task is how to select a subset of possible BS sites, including macro BSs, pico BSs and relay nodes, to minimize the total deployment cost while satisfying all rate requirements of demand nodes. We develop an approximation algorithm to tackle the formulated NP-hard problem, which guarantees an approximation ratio of O(log R) to the optimal solution, where R is the maximal achievable capacity of BSs.

There has been a growing interest in analog network coding, which can improve system throughput and spectrum efficiency significantly in wireless systems. Two-way relay scenario is considered in this paper, where the base station (BS) and the relay are both equipped with multiple antennas, and each of K user equipments (UEs) in the cell has a single antenna. An advanced multi-user scheduling scheme is proposed for the analog network coded two-way relay channel, where UEs and BS exchange information via the relay node during two time slots. Because each UE with single antenna has poor transmission and reception capability, the scheduling scheme is carefully designed to decrease multi-user interference and optimize beamforming gain from BS to relay. Analytical results of sum rate and outage probability have been developed to demonstrate that the multi-user diversity gain can be achieved by the proposed scheme. Meanwhile, the user fairness of the proposed scheme is on the same order as that of round robin (RR), and the computation complexity only increases linearly with the number of users in the serving cell. Monte-Carlo simulation is conducted to exhibit the performance gains from the proposed scheduling scheme. Results show that the proposed channel correlation based user selection scheme outperforms existing traditional scheduling schemes significantly, even when the cellular user payload is low.

This paper presents the link-level performance of downlink non-orthogonal multiple access (NOMA) with successive interference cancellation (SIC) receiver, considering the influence of error vector magnitude (EVM). In our evaluations, for the case of a 1-by-2 transmission and the number of NOMA multiplexed users is two, we clarify the performance of NOMA for cell-center user equipment (UE) with codeword level SIC (CWIC) receiver and the performance of the cell-edge UE, which does not apply SIC. Based on link-level performance evaluations, we show that the performance of CWIC receiver is almost the same as that of ideal SIC when the allocated transmit power ratio to cell-center UE is less than 0.35, the modulation and coding scheme (MCS) of cell-center UE is 16QAM (R = 0.51) or 64QAM (R = 0.47), and the MCS of cell-edge UE is QPSK (R = 0.51). Furthermore, we also show that, when EVM value is 4 % and the allocated power ratio to cell-center UE is between 0.2 and 0.37, the level of degradation due to the influence of EVM is below 0.6 dB, which is almost the same level of degradation as that of orthogonal frequency division multiple access (OFDMA) for the EVM value required by 3rd Generation Partnership Project (3GPP) Long Term Evolution (LTE). On the other hand, we show that the influence of EVM is marginal for cell-edge UE compared to cell-center UE. However, when the cell-center UE uses a higher order modulation such as 64QAM, we show that the required SNR of cell-edge UE increases due to the increase in inter-user interference. Based on these results, we clarify that it is important for the base station (BS) to take into account the target BLER and influence of EVM when selecting the MCS and allocated transmit power ratio of NOMA UEs.