Dynamic Spectrum Allocation Scheme for Heterogeneous Network

The heterogeneous network (HetNet) is a promising network for beyond 5G to improve network capacity and spectral efficiency by developing low-power small cells within macro networks. Therefore, appropriate resource allocation schemes should be designed to balance between data rates and the cross-tier interference among different cells. To improve system robustness and also reduce the harmful interference to macrocell users (MUs), in this paper, we maximize the total interference efficiency (IE) (i.e., the ratio of the sum data rates of femtocell users (FUs) to the total cross-tier interference from femtocell base stations (FBSs) to MUs) with imperfect channel state information in a two-tier orthogonal frequency division multiple access based HetNet by jointly optimizing the transmit power of the FBS and the subcarrier allocation factor. Meanwhile, the outage rate constraint of each FU, the outage interference constraint of each MU, the maximum transmit power constraint of the FBS, and the subcarrier assignment constraint are considered simultaneously. The considered problem belongs to a mixed-integer non-linear programming problem and thus is NP-hard. The original problem with uncertain parameters is transformed into a deterministic and convex one solved by using the quadratic transformation approach, the variable relaxation approach, and Lagrange dual theory. The feasible region analysis and robust sensitivity are provided. Simulation results demonstrate that the proposed scheme has a lower interference to the MU and higher IE by comparing it with the traditional schemes.

This paper presents an alternative to existing dynamic spectrum allocation (DSA) schemes, in a flexible spectrum licensing environment where multiple networks coexist and interfere with each other. The proposed virtually bounded DSA scheme (VBS) takes a different approach to fairly manage the spectrum resources in response to temporal deviation in spectrum demands. In particular, a new concept of dynamic virtual boundary is introduced. Based on this concept, the VBS dynamically adjusts the virtual boundaries of spectrum blocks dedicated for the primary systems to reduce the occurrences where the insertion of guard bands is obligatory and consequently provides better spectral efficiency than existing Fragmented and Contiguous DSA schemes.

In this paper, an adaptive and self-organizing spectrum allocation policy for ad hoc femtocells in two-tier networks based on usage of random frequency hopping is presented. As femto- and macrocells normally share the same frequency resources, the proposed approach is able to minimize InterCell Interference (ICI) in an adaptive manner. Each femto- and macrocell user chooses random carrier frequencies for transmission corresponding to a given probability density function (pdf). If the level of interference reaches a certain limit, which is typically the case for femtocell edge users, the probability density function of the carrier frequencies is changed in a way that it is quasi-orthogonal to the one of the macrocell users nearby. The changeover point between different probability density functions is realized in a self-organizing manner regarding the detected level of interference. Hence, the approach is able to adjust the trade-off between spectral efficiency and introduced interference during operation. We present analytical models for the Signal-to-Interference-and-Noise-Ratio (SINR), the Bit Error Ratio (BER) and the required transmission power of Orthogonal Frequency Division Multiple Access (OFDMA) femtocells applying adaptive random frequency hopping. The mobile radio channel is characterized by non-frequency selective Rayleigh fading and all results are verified by simulations implemented in MATLAB. In order to evaluate the improvements, the results are compared to systems using centralized orthogonal planning, systems using neither centralized nor distributed planning, and systems using static random frequency hopping. The comparison shows that adaptive random frequency hopping is capable of reducing the BER by a factor of 15 and the transmission power of femtocells by 17 dBm compared to systems where the macrocell user transmits in the same subbands as the femtocell user.

This paper presents a framework for allocating radio resources to the Access Points (APs) introducing an Access Point Controller (APC). Radio resources can be either time slots or subchannels. The APC assigns subchannels to the APs using a dynamic subchannel allocation scheme. The developed framework evaluates the dynamic subchannel allocation scheme for a downlink multicellular Orthogonal Frequency Division Multiple Access (OFDMA) system. In the considered system, each AP and the associated Mobile Terminals (MTs) are not operating on a frequency channel with fixed bandwidth, rather the channel bandwidth for each AP is dynamically adapted according to the traffic load. The subchannels assignment procedure is based on quality estimations due to the interference measurements and the current traffic load. The traffic load estimation is realized with the measurement of the utilization of the assigned radio resources. The reuse partitioning for the radio resources is done by estimating mutual Signal to Interference Ratio (SIR) of the APs. The developed dynamic subchannel allocation ensures Quality of Service (QoS), better traffic adaptability, and higher spectrum efficiency with less computational complexity.

Cognitive Femtocell Networks(CFNs) has been envisioned as a promising technology to provide high data rate and better coverage simultaneously. However, the existing spectrum allocation problem cannot ensure the true requirement and effectiveness for CFNs. A new dynamic spectrum allocation scheme with reputation model (DSA-RM) is proposed in this paper, in which core-selecting auction is adopted to solve the Winner Determination Problem and minimize femtocell user's incentive for deviating from truthful-telling. The analysis results show that the algorithm can effectively prevent the user from cheating at the time of applying for spectrum resources and improve the spectrum efficiency.

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Orthogonal Frequency-Division Multiple Access (OFDMA) has emerged as an advanced technique to enhance resource utilization and efficiency in infrastructure-based networks. However, its performance in wireless mesh networks is mostly unexplored. In this paper, we practically study the benefits of OFDMA in a scenario with multiple co-located transmitters and receivers without centralized controller by means of the software-defined radio platform WARP. We propose five different dynamic subchannel allocation strategies and compare their performance to that of OFDM as a baseline. Four of these strategies are constrained to be fair with respect to the number of subchannels allocated per communication link, while the fifth always allocates a subchannel to its best possible communication link. By means of testbed experiments with software-defined radios, we show that the overall bit error rate can be reduced by a factor of ten, while the overall channel capacity can locally be enhanced by 10% to 30%. Further, we use the Subchannel Avoidance Gain as a metric to quantify the ability of a dynamic subchannel allocation strategy to avoid subchannel allocations resulting in poor channel conditions.

This article investigates resource allocation in ATM networks and emphasizes bandwidth allocation. Resource allocation methods are categorized, and static and dynamic allocation strategies are compared. Dynamic allocation uses actual traffic behavior, while static allocation uses only the reference traffic condition given a priori. Examples of dynamic allocation strategies are available bit rate flow control, dynamic connection admission control, and dynamic VP bandwidth control. Dynamic resource allocation is shown to be promising for situations where the a priori reference model is unclear.

Interference management is important in wireless cellular networks such as long-term evolution (LTE) and LTE-A, where orthogonal frequency division multiple access (OFDMA), dense frequency reuse and heterogeneous cell sizes and capabilities provide great performance at the cost of increased network complexity. The layered structures of emerging cellular networks and their dynamic environments limit greatly the efficacy of traditional static interference management methods. Furthermore, conventional interference coordination techniques assume that perfect channel knowledge is available and that the signalling overhead can be neglected. In this paper, we analyse a heterogeneous LTE OFDMA downlink network composed by macro-, pico- and femtocells. We propose a low-complexity, distributed and cooperative interference mitigation method which is aware of network load and propagation conditions. The proposed method is fully scalable and addresses the interference received by the macro and pico layer and the interference received by femtocells separately. The new solution makes use of the iterative Hungarian algorithm, which effectively reduces interference and enhances the quality of service of starved users when compared to other state-of-the-art solutions. The proposed method outperforms static solutions by providing comparable results for the cell edge users (the proposed solution delivers 86% of the gain of a static frequency reuse 3) while presenting no loss at the cell centre, compared to an 18% loss of the frequency reuse 3 in a homogeneous scenario. In a heterogeneous network (HetNet) deployment, it generates a gain of 45% for the combined macro and pico edge users at a very small cost for the cell centre lower than 4% when compared with standard resource allocation. It optimizes greatly picocell performance, with improvements of more than 50% at a small cost for femtocell users (15%). In order to apply the proposed method to a practical network, the impact of the necessary quantization of channel state information on the interference management solution is studied and results show that signalling overhead can be contained while performance is improved by increasing resolution on the portions of the bandwidth more likely to be assigned to the users.

QoS-aware distributed spectrum sharing for heterogeneous wireless cognitive networks

The Non-Orthogonal Multiple Access (NOMA) and the Orthogonal Frequency Division Multiple Access (OFDMA) are promising techniques for next-generation wireless systems. Although much attention in the literature considered these techniques, an effective combination between such systems as hybrid multiple access (HMA) needs more attention. For this reason, this paper devotes to proposing two different scenarios of HMA using multi-user OFDM (MU-OFDM) and power domain (PD) NOMA for downlink transmission to overcome the limitations of both Orthogonal Multiple Access (OMA) and NOMA. Due to the randomness of a wireless channel, different user grouping strategies and dynamic power allocation (DPA) strategies are employed to satisfy users’ requirements. The proposed systems give high flexibility utilizing bitrate allocation and user fairness. System results show superior performance to traditional OMA and NOMA systems. The achieved variety of fairness is helpful for the diversity of applications which is a principal requirement for beyond-fifth-generation (B5G) networks. The next step in this analysis is to enhance the proposed systems’ spectral efficiency (SE) by introducing beamforming for massive Multiple-Input Multiple-Output (MIMO) systems. The bit error rate (BER) result of the proposed system achieves almost the same error floor with a benefit of approximately 10 dB signalto-noise ratio (SNR) when 90 resource blocks (RBs) are used.

Orthogonal Frequency Division Multiple Access (OFDMA) is a promising technique which can provide high capacity in the wireless environments. Also cooperative communications are effectively used to achieve cooperative diversity for high reliability. In this paper, we propose the pair-based OFDMA frame structure in which cooperative users transmit their blocks in turns for achieving cooperative diversity in OFDMA systems. In order to guarantee the fairness of users we also propose a dynamic resource allocation scheme based on cooperative communications. Through the proposed scheme, user fairness can be achieved by sharing the remained capacity of users near the base station (BS) with users who are farther from the base station. For this purpose, the center-located users select their partner whose channel suffers the lowest SNR to BS among their neighbor set. Based on the partner selection results, subchannels are assigned to cooperative and non-cooperative users. Through simulations in the IEEE 802.16e system environments, it is shown that the proposed scheme outperforms the non-cooperation based scheme in terms of user fairness.

Cognitive radio networks (CRNs) have been widely studied to improve spectrum utilization through a dynamic spectrum allocation scheme. However, many challenges remain and one big issue is how to provide an efficient spectrum management in a mobile environment. In this paper, we propose a new prediction-based spectrum management strategy to tackle this challenge. Both spectrum prediction and users’ mobility prediction are fully considered in the proposed strategy. Combining the prediction information and cooperative sensing, a CR base station can obtain the sensing information for future location of each secondary user, so as to prearrange high-quality channels for secondary users ahead of time. In addition, we propose a new channel selection scheme when multiple channels are available simultaneously. Besides traditional decision factors, the new channel selection algorithm takes the channel's future availability obtained from spectrum prediction into account. By properly integrating the spectrum prediction, user mobility prediction, and channel selection, the new spectrum management strategy is capable of allocating the spectrum resource more efficiently. Extensive simulations are conducted and results verify that the proposed spectrum management strategy significantly improves the system performance in terms of reducing handoff times and improving user satisfactory, connection reliability, and channel utilization.

In this paper, we propose a joint resource allocation, routing, and connection admission control (CAC) scheme for uplink transmission in orthogonal frequency division multiple access (OFDMA) relay networks with cooperative relaying. For cooperative relaying, relay station can relay uplink data from mobile station (MS) to base station with cooperation of the MS using transmit diversity. Transmit diversity can be achieved by virtual MISO via distributed space---time coding. The proposed scheme jointly allocates OFDMA resources and selects path for each user with CAC to maximize the upink throughput of cooperative OFDMA relay networks. The basic OFDMA resource unit is considered as a resource element which is one subcarrier over one OFDMA symbol. An efficient multi-choice multi-dimensional knapsack (MMKP) algorithm is presented for the proposed scheme. The proposed MMKP algorithm provides a unified framework which is applicable to OFDMA networks with and without cooperative relaying. We evaluate the performance of the proposed scheme with and without cooperative relaying in a hilly terrain with heavy tree density by using OPNET-based simulation. We show that the cooperative relaying improve the uplink system throughput compared with non-cooperative relaying, and the proposed scheme outperforms the conventional link quality-based scheme in both cooperative and non-cooperative relay networks.

The paper describes a Resource allocation in cellular networks using orthogonal frequency division multiple access (OFDMA) systems. Both center cell and edge cell users using same power, edge cell users suffer from Inter Cell Interference (ICI). Power allocation cell-edge user's power is maximized automatically reduce the inter cell interference under the condition that desirable performance for cell-center users must be maintained. The power optimization is formulated as a Greedy Power allocation method. Simulation results indicate that our proposed scheme can achieve significantly balanced performance improvement between cell-edge and cell-center users in multi-cell networks, and goal of future wireless networks in terms of providing high performance to anyone from anywhere.