Spectral Efficiency Of Cellular Networks Research Articles

Uplink Cooperative Interference Cancellation for Cellular-Connected UAV: A Quantize-and-Forward Approach

Aerial-ground interference is the main obstacle to achieving high spectral efficiency in cellular networks with both traditional terrestrial users and new unmanned aerial vehicle (UAV) users. Due to their strong line-of-sight (LoS) channels with the ground, UAVs could cause/suffer severe interference to/from a large number of non-associated but co-channel base stations (BSs) in their uplink/downlink communications. In this letter, we propose a new cooperative interference cancellation (CIC) scheme for the UAV's uplink communication to mitigate its strong interference to co-channel BSs, which requires only local cooperation between each co-channel BS and its adjacent helping BSs. Specifically, the helping BSs without serving any users in the UAV's communication channel quantize and forward their received signals from the UAV to their aided co-channel BS, which then processes the quantized signals jointly with its own received signal to decode its served terrestrial user's message via canceling the UAV's signal by linear/nonlinear interference cancellation techniques (ICTs). We derive the achievable rates of the proposed CIC scheme with different ICTs as a function of the UAV's transmit power and rate, and thereby unveil the conditions under which the proposed CIC scheme outperforms the existing CIC scheme based on the decode-and-forward (DF) operation of the helping BSs.

Pair Auction and Matching for Resource Allocation in Full-Duplex Cellular Systems

Full-duplex techniques improve spectral efficiency in cellular networks by allowing a transceiver to simultaneously transmit and receive data with the same radio resource. To minimize self-interference and inter-node interference due to the deployment of full-duplex radio, users have to feed back their measurements of interference to allow the base station to effectively allocate resources and form transmission pairs. Considering that the interference measurements are private information, users may not report the true values and may try to gain their own benefits. To solve this problem, we propose a strategy-proof resource allocation mechanism for full-duplex cellular networks. The proposed scheme, which is based on auction and matching theories, guarantees that users report true values of their channel quality and utilities, and therefore guarantees the correctness of feedback information and the efficiency of resource allocation. Moreover, the proposed matching-based mechanism is theoretically proved to be stable and Pareto efficient. Simulation results confirm that, compared to a centralized scheme with non-truthful information from users, the proposed scheme can achieve an 11 $\%$ gain.

Performance Analysis of D2D-Aided Underlaying Cellular Networks Based on Poisson Hole Cluster Process

D2D (Device-to-Device) communication has become a crucial part of 4G and 5G networks. It can not only decrease the transmit power of user equipments (UEs) and increase area spectral efficiency of cellular networks, but also offload traffic from cellular networks and alleviate scarcity of spectrum resources by using in-band communication. In this paper, we consider a real tele-communication scenario in which the mobile UEs are primarily located in hotspots and cell edges. By integrating Poisson Hole Process with Thomas Cluster Process, a kind of D2D-Aided Underlaying Cellular Networks (D2D-UCNs) is built. In the D2D-UCNs, we first investigate the aggregation interference of the typical UE and D2D user by using stochastic geometry. Subsequently we analyze their coverage probability and area spectral efficiency. The simulation results show that the coverage probability of D2D users and UEs can be effectively guaranteed by establishing exclusion zone, whilst the area spectral efficiency of the D2D-UCNs can be maximized by optimizing the number of simultaneously active D2D links.

Energy Efficient Power and Channel Allocation in Underlay Device to Multi Device Communications

In this paper, we optimize the energy efficiency (bits/s/Hz/J) of device-to-multi-device (D2MD) wireless communications. While the device-to-device scenario has been extensively studied to improve the spectral efficiency in cellular networks, the use of multicast communications opens the possibility of reusing the spectrum resources also inside the groups. The optimization problem is formulated as a mixed integer non-linear joint optimization for the power control and allocation of resource blocks (RBs) to each group. Our model explicitly considers resource sharing by letting co-channel transmission over a RB (up to a maximum of r transmitters) and/or transmission through s different channels in each group. We use an iterative decomposition approach, using first matching theory to find a stable even if sub-optimal channel allocation, to then optimize the transmission power vectors in each group via fractional programming. Additionally, within this framework, both the network energy efficiency and the max-min individual energy efficiency are investigated. We characterize numerically the energy-efficient capacity region, and our results show that the normalized energy efficiency is nearly optimal (above 90 percent of the network capacity) for a wide range of minimum-rate constraints. This performance is better than that of other matching-based techniques previously proposed.

Hypergraph Theory: Applications in 5G Heterogeneous Ultra-Dense Networks

Heterogeneous ultra-dense networks (HUDNs) can significantly increase the spectral efficiency of cellular networks and cater for the explosive growth of data traffic in 5G communications. Due to the dense deployment of small cells, interference among neighboring cells becomes severe. As a result, effective resource allocation and user association algorithms are essential to minimize inter-cell interference and optimize network performance. However, optimizing network resources in an HUDN is extremely complicated as resource allocation and user association are coupled. Therefore, an HUDN requires low-complexity but effective resource allocation schemes to address these issues. Hypergraph theory has been recognized as a useful mathematical tool to model the complex relations among multiple entities. In this article, we show how the hypergraph models can be used to effectively tackle resource allocation problems in an HUDN. We also discuss several potential research issues in this field.

Distributed radio resource allocation for device-to-device communications underlaying cellular networks

Underlaying Device-to-Device (D2D) communications can increase the spectral efficiency of cellular networks when sharing part of the spectrum with cellular users. This requires radio resource allocation policies capable to limit and control the interference between D2D and cellular communications. Many of the proposed policies are centralized, and require the base station to decide which resources should be allocated to each D2D transmission. Centralized schemes can efficiently control interference levels, but their feasibility can be compromised by their complexity and signaling overhead. To address this constraint, this paper proposes DiRAT, a distributed radio resource allocation scheme for D2D communications underlaying cellular networks. With DiRAT, the D2D nodes locally select their radio resources from a pool created by the cellular network in order to control the interference generated to the primary cellular users. DiRAT includes a control mechanism to ensure that the user QoS requirements are satisfied. This study demonstrates that DiRAT can increase the network capacity while avoiding or limiting the degradation of the performance of the primary cellular users. DiRAT also significantly reduces the complexity and overhead compared to existing centralized and distributed schemes.

Distributed Energy-Spectrum Trading in Green Cognitive Radio Cellular Networks

Reducing the power consumption of base stations is crucial to enhancing the energy efficiency of cellular networks. As the number of mobile users increases exponentially, enhancing the spectrum efficiency is also critical in order to accommodate more users. In this paper, by exploiting the cooperation between secondary base stations (SBSs) and primary base stations (PBSs), we propose a new energy spectrum trading model to enhance the energy as well as spectrum efficiency of cellular networks. In our scheme, by leveraging cognitive radio, PBSs share some portion of their licensed spectrum with SBSs, and SBSs, in exchange, provide data service to the primary users under their coverage. We first prove that the power consumption minimization problem is NP-hard. Then, to decrease the computational complexity, we design an efficient distributed auction model including green energy aware bidding (GEAB) and adaptive bid selection (ABS) algorithms, to achieve a good approximation of the optimal solution in less time. Our simulation results show that the cooperation between PBS and SBSs via ABS and GEAB algorithms can significantly improve the energy and spectral efficiency of cellular networks by nearly doubling the number of offloaded users and reducing the PBS power consumption by up to 40% as compared to existing approaches. Furthermore, green energy utilization among SBSs is increased by nearly 25%.

Ergodic Spectral Efficiency in MIMO Cellular Networks

This paper shows how the application of stochastic geometry to the analysis of wireless networks is greatly facilitated by (i) a clear separation of time scales, (ii) the abstraction of small-scale effects via ergodicity, and (iii) an interference model that reflects the receiver's lack of knowledge of how each individual interference term is faded. These procedures render the analysis both more manageable and more precise, as well as more amenable to the incorporation of subsequent features. In particular, the paper presents analytical characterizations of the ergodic spectral efficiency of cellular networks with single-user multiple-input multiple-output (MIMO) and sectorization. These characterizations, in the form of easy-to-evaluate expressions, encompass the coverage, the distribution of spectral efficiency over the network locations, and the average thereof.

Energy and Spectral Efficiency of Cellular Networks With Discontinuous Transmission

Cell discontinuous transmission (DTX) has been proposed as a solution to reduce the energy consumption of cellular networks. This paper investigates the impact of network traffic load on the spectral and energy efficiency of cellular networks with DTX. The signal-to-interference-plus-noise ratio (SINR) distribution as a function of traffic load is derived first. Then, the sufficient condition for ignoring thermal noise and simplifying the SINR distribution is investigated. Based on the simplified SINR distribution, the network spectral and energy efficiency as functions of network traffic load are derived. It is shown that the network spectral efficiency increases monotonically in traffic load, while the optimal network energy efficiency depends on the ratio of the sleep-mode power consumption to the active-mode power consumption of base stations. If the ratio is larger than a certain threshold, the network energy efficiency increases monotonically with network traffic load and is maximized when the network is fully loaded. Otherwise, the network energy efficiency first increases and then decreases in network traffic load. The optimal load can be identified with a binary search algorithm. The power ratio threshold depends solely on the path loss exponent $\alpha$ , e.g., 56% for $\alpha = 4$ . All these analytic results are further validated by the numerical simulations.

Spectrum Reuse Schemes with Power Control for Device-to-Device Communication in LTE-Advanced Cellular Network

The spectral efficiency of cellular networks can be improved when proximate users engage in device-to-device (D2D) communications to communicate directly without going through a base station. However, D2D communications that are not properly designed may generate interference with existing cellular networks. In this paper, we study resource allocation and power control to minimize the probability of an outage and maximize the overall network throughput. We investigate three power control-based schemes: the Partial Co-channel based Overlap Resource Power Control (PC.OVER), Fractional Frequency Reuse based Overlap Resource Power Control (FFR.OVER) and Fractional Frequency Reuse based Adaptive Power Control (FFR.APC) and also compare their performance. In PC.OVER, a certain portion of the total bandwidth is dedicated to the D2D. The FFR.OVER and FFR.APC schemes combine the FFR techniques and the power control mechanism. In FFR, the entire frequency band is partitioned into two parts, including a central and edge sub-bands. Macrocell users (mUEs) transmit using uniform power in the inner and outer regions of the cell, and in all three schemes, the D2D receivers (D2DRs) transmit with low power when more than one D2DRs share a resource block (RB) with the macrocells. For PC.OVER and FFR.OVER, the power of the D2DRs is reduced to its minimum, and for the FFR.APC scheme, the transmission power of the D2DRs is iteratively adjusted to satisfy the signal to interference ratio (SIR) threshold. The three schemes exhibit a significant improvement in the overall system capacity as well as in the probability of a user outage when compared to a conventional scheme.

Sociality‐aware resource allocation for device‐to‐device communications in cellular networks

Exploiting direct transmissions between geographically close mobile users without passing through the base stations, device-to-device (D2D) communications contribute significant improvement to the spectral efficiency of cellular networks. In D2D-assisted cellular networks, the social interaction of mobile users is an important property that will affect the practical performance and should be seriously accounted in the network resource allocation, which is yet to be fully explored. In this study, the authors investigate the social interactions for D2D transmissions and develop a contact time model to characterise the D2D links. A D2D link can be considered for resource allocation only when the two users encounter and their contact time is enough long to complete a meaningful transmission. They formulate and compare both sociality-blind and sociality-aware optimisation problems for resource allocation in D2D-assisted cellular networks. Extensive numerical results are presented, validating that the sociality-aware resource allocation can achieve higher performance than that of the sociality-blind approach.

Enhancing spectral efficiency for lte-advanced and beyond cellular networks [Guest Editorial

The rapidly growing demands for bandwidth-intensive mobile broadband services have triggered tremendous efforts to develop the long-term-evolution (LTE)-Advanced and beyond cellular networks, which are widely deemed as a major advancement of the existing LTE networks. Constrained by limited spectral resources, wireless communication researchers and engineers have proposed a number of technologies to efficiently utilize spectral resources in multiple dimensions. Specifically, with a large number of transmit antennas deployed at a base station, massive multiple-input multiple- output (MIMO) (also called full-dimension MIMO [FD-MIMO] in the Third Generation Partnership Project [3GPP] community) is expected to achieve enormous spectral efficiency by exploiting degrees of freedom in the spatial domain. Recent theoretical and experimental findings highlight that massive MIMO is a promising solution to improve data rates , link reliability, and power savings for cellular networks. Another attractive technology, small cells, has also shown great potential for enhancing system throughputs of LTE-Advanced and beyond cellular networks. In the small cell solution, lower-cost base stations are densely deployed, and the size of a cell is substantially reduced, thus enabling great improvement of frequency reuse ratios in the geographical domain and significant enhancement of the spectral efficiency of cellular networks. Also, other technologies such as deviceto-device (D2D) and cognitive radio have also emerged as promising solutions to boost the spectral efficiency of cellular networks in various scenarios.

Subspace Quantization Based Combining for Limited Feedback Block-Diagonalization

Spatial multiplexing of multiple users in a multi-antenna broadcast system, i.e., multi-user MIMO, is a promising technique for improving the spectral efficiency of cellular networks. Still, practical implementations struggle with the difficulty of obtaining sufficiently accurate channel state information at the transmitter (CSIT), due to restrictions on the capacity of the CSI feedback links from the users. Without accurate CSIT, residual multi-user interference diminishes the potential performance gain of multi-user MIMO, challenging its value for practical realizations. In this work we show that the CSI feedback overhead can be significantly reduced if the number of spatially multiplexed data streams per user is less than the number of receive antennas, and the antenna outputs are appropriately combined. We propose an interference-unaware antenna combining algorithm that minimizes the CSI quantization error, which has the effect of minimizing multi-user interference at the price of reducing the received signal power. We mathematically analyze the performance of the proposed algorithm, substantiating its value for limited feedback systems. Numerical simulations confirm the potential of the proposed algorithm in comparison to a traditional technique that maximizes the received signal power.

QoS and Channel-Aware Packet Bundling for Capacity Improvement in Cellular Networks

We study the problem of multiple-packet bundling to improve spectral efficiency in cellular networks. The packet size of real-time data, such as voice over Internet Protocol (VoIP), is often very small. However, the common use of time-division multiplexing (TDM) limits the number of VoIP users supported because a packet has to wait until it receives a time slot, and if only one small VoIP packet is placed in a time slot, capacity is wasted. Packet bundling can alleviate such a problem by sharing a time slot among multiple users. A recent revision of cdma2000 1xEV-DO has introduced the concept of the multiuser packet (MUP) in the downlink to overcome limitations on the number of time slots. However, the efficacy of packet bundling is not well understood, particularly in the presence of time-varying channels. We propose a novel quality-of-service (QoS) and channel-aware packet bundling algorithm that takes advantage of adaptive modulation and coding. We show that optimal algorithms are nondeterministic polynomial time (NP)-complete, recommend heuristic approaches, and use analytical performance modeling to show the gains in capacity that can be achieved from our packet bundling algorithms. We show that channel utilization can be significantly increased by slightly delaying some real-time packets within their QoS requirements while bundling those packets with like channel conditions. We validate this paper through extensive OPNET simulations with a complete evolution-data optimized (EV-DO) implementation.