In this paper, we present a power allocation technique that improves the sum rate and energy efficiency without reducing the minimum data rate of an established resource block allocation technique. To achieve this, the technique is implemented in two stages where the first is for ensuring that the minimum data rate remains unchanged. The second stage is for increasing the sum rate by ensuring that more resource blocks are reused by the femtocells that reduce their power. The algorithm is iterative with changes in transmit power resulting in changes in resource block allocation. It will be shown that at the expense of some delay, the proposed technique can result in significant energy savings while maintaining the minimum data rate when compared to equal power allocation. Further, relative to optimal allocation techniques, the proposed technique results in better fairness.

Channel correlation between different users can significantly deteriorate the energy and spectral efficiency of massive MIMO systems. As such, it is tempting to separate the highly correlated users in order to reduce intra-cell interference to improve the overall system performance. In this respect, and unlike existing work, we propose an adaptive user grouping algorithm for the downlink of multiuser massive MIMO systems where users are grouped based on the values of their correlation coefficients. The proposed algorithm is adaptive in the sense that the number of neither the groups nor the users of each group is fixed. Furthermore, the grouping process relies on finding the correlation coefficients that are larger than a certain threshold value and isolating their corresponding users in separate groups which are served in different scheduled time. The threshold value is variable and can be adjusted to achieve the best performance compared to the non grouping scenario. The results reveal that the proposed system can considerably enhance the sum rate performance relative to the non-grouping case for the same bandwidth requirements.

This paper proposes a solution to enhance the performance of femtocell networks. We focus on studying the capacity and QoS behavior of femtocell deployment by utilizing a joint cellular association and resource partitioning strategy. A novel method is proposed to maximize the reuse efficiency by careful partitioning of the frequency resources, such that the interfering parties do not overlap. A cellular association scheme is also developed to improve the resource utilization further, by accurate identification of the association pairs with the potential to increase the reuse efficiency, while taking into consideration several factors such as cell load, the received signal power and the availability of resources. To ensure efficient utilization of the additional resources, the association scheme is combined with the interference aware resource partitioning. For validation purposes, the performance of the proposed scheme is evaluated and compared with the standard Max-RSS Cellular association.The simulation results show good overall performance when compared with the standard association scheme.

This paper proposes an adaptive scheduling strategy to improve the energy efficiency of massive MIMO. The proposed technique combines a novel adaptive discontinuous transmission (ADTx) and antenna optimization that can optimize the number of active antennas and transmission period such that data can be delivered to users with the minimum power. The proposed ADTx utilizes a DTx principle and adaptive precoding technique selection. On the other hand, antennas optimization is used to relax the number of active antennas once the required period has been calculated. Although massive MIMO is initially designed to utilize the multiplexing users found in dense users scenario, this paper discusses the impact of the proposed technique to low density scenarios, in particular suburban scenario, because major parts of cellular coverage are low density. It will be shown that the proposed scheme provides significant energy efficiency (EE) and QoS improvement that can support green cellular network.

This paper addresses energy efficiency (EE) of large scale antenna systems (LSAS) or massive MIMO based cellular networks. We propose a joint technique that combines a novel successive discontinuous transmission (SDTx) scheme with antenna array optimization (AAO). The SDTx utilizes information regarding the users' requirements and properties to deliver data efficiently and without compromising the users' service. On the other hand, AAO further reduces power consumption through minimizing the number of active antenna elements. Users requirements include bit rate and latency requirement while the users properties include pathloss between users and macro base station (MBS) and users' movement. It will be shown that, relative to conventional LSAS, the proposed scheduling significantly improves the EE of LSAS network for various network load under practical users' requirement in dense urban environment making it a potential candidate for green cellular networks.

Switching off base stations is a popular approach to improving the energy efficiency a network. The challenge is how to determine which and how many base stations to switch off given a network configuration while ensuring that the network coverage is not compromised. Different algorithms have been formulated to solve this challenge ranging from load-aware algorithms to random selection. Results show that load-aware algorithms have better performance. Most algorithms assume universal frequency reuse by all base stations even in the case of heterogeneous networks. In this paper we assume an indoor, femtocell network where subcarrier allocation is based on an existing subcarrier allocation technique which ensures maximum reuse. A load-aware base station switch-off algorithm is developed that uses the allocation matrix when all base stations are active and an estimate of required subcarriers by each base station to determine which base stations to switch off. It will be shown that even without any power control, the proposed technique can result in significant energy savings for lower femtocell densities.

Femtocell technology is widely known for its ability to improve cellular services while reducing the capital and operation expenditure of cellular providers. However, this can lead to more interference and accessibility issues. There are three types of femtocell access schemes currently, which are open, closed and hybrid access. While open access improves the overall network performance, closed access is a much more preferred by the end-user since it guarantees access to the femtocell owner. For this reason, hybrid access is a compromise which releases the femtocell access to the visitor when there is surplus resource left by the owner. This paper proposes a comprehensive method to solve the femtocell access issue by designing a joint multilevel priority scheduling and femtocell access policy based on a Matrix of Conflict RRM. It will be shown through computer simulation that the proposed scheduling and access policy provide network flexibility, for the femtocell owner and cellular provider, which can be utilized to achieve more benefits for both.

This paper proposes and analyses a new cooperative diversity technique that combines users pairing and interference exploitation for enhancing the performance of asynchronous uplink transmission in OFDMA based systems. As well as achieving a diversity order of two, the proposed technique attains further performance enhancements by exploiting co-channel interference. The impact of the proposed technique on various asynchronous conditions is considered in this paper and the performance is assessed through simulation and mathematical analysis. Combined with an effective interference cancellation technique, it will be shown that the results from both models closely match and demonstrate that a significant performance enhancement is obtained relative to other schemes for OFDMA uplink transmission.

This paper proposes a new pairing cooperative technique to achieve spatial diversity and constructive interference exploitation in uplink orthogonal frequency-division multiple access (OFDMA) systems. The underlying principle is to pair users such that their symbols are combined into a single constellation, according to a predefined rule, so that the same symbol is transmitted by each pair of users so their signals can be coherently summed at the receiver, hence maximizing the received signal power. To achieve such constructive combination of both signal copies, single-dimensional OFDMA is utilized in the inphase and quadrature dimensions. It will be shown that such transmission method not only maximizes the received power but also greatly reduces sensitivity to timing misalignment between the cooperating users. Both time synchronous and asynchronous transmission scenarios will be considered. In the asynchronous case, interference reduction will be applied at the base station to reinstate the pairs' orthogonality and hence minimize co-channel interference. The performance of this technique is evaluated through simulations and mathematical analysis. It will be shown that the results from both models closely match and that the proposed technique provides significant bit-error-rate reductions, particularly at low signal-to-noise ratio, and throughput improvements relative to existing cooperative transmission techniques.

A new radio resource management (RRM) technique for improving the downlink performance in soft-frequency-reuse based long term evolution (LTE) networks is presented. In this RRM the resource is dynamically allocated in distributed and centralized manners such that spectral efficiency is maximized across the whole network. To achieve this a unique interference mapping strategy is implemented to assist in deciding whether a distributed or centralized mode is applicable per basestation. When a distributed approach is granted to a basestation it can use the entire spectrum while when a centralized approach is imposed on a basestation it will only be allocated a subset of the spectrum. The proposed then utilizes the confederation concept in the sense that once the allocation approach is determined the individual basestations can take control of their allocated resource. When combined with proportional fairness scheduling, this RRM can also benefit from multiuser diversity. It will be shown through mathematical analysis and computer simulations that this technique offers significant improvements in terms of sum rate and quality of service by increasing the guaranteed data rate per user.

This paper proposes a new resource management algorithm that utilizes the self-organizing network functionality for optimising spectrum usage and minimising cross-tier interference between macrocell and femtocells and co-tier interference between femtocells. To achieve this, the proposed algorithm dynamically maximizes usage of all the available subcarriers by exploiting knowledge of the interference power at each user. Taking into account the associated overhead and power consumption it will be shown that the proposed algorithm improves the average data rate per user as well as the energy efficiency of femtocells networks in all femtocell density scenarios, and, is also superior to existing techniques. The fact that the proposed RRM minimizes the energy efficiency and maximizes the average data rate makes it an ideal contender for adoption in future green heterogeneous wireless networks.

This paper proposes an adaptive radio resource management (RRM) algorithm based on self-organizing network (SON) and distance vector routing protocol (DVRP) strategy for power consumption reduction and quality of service (QoS) improvement in long term evolution (LTE) network. Using SON principle, the base stations downlink transmissions can be effectively organized to maximise interference avoidance. Combining with DVRP routing strategy for enhance resource allocation, it will be shown that the proposed strategy is capable to adaptively adjust the power consumption of the BS and support the increasing demand on QoS per user in LTE cellular network.

This paper proposes and analyzes a new cooperative diversity technique that combines users pairing and interference exploitation for enhancing the uplink transmission performance in uplink OFDMA systems suitable for 4G technology. The underlying principle is to pair users on the basis of best interuser channel by utilizing low transmit power communication in the unlicensed band to exchange data symbols. Then, each pair remap their combined symbols according to a predefined rule such that they transmit the same constellation using single dimensional OFDMA to ensure that the signals of each pair combine constructively at the destination. As well as achieving a diversity order of two, the proposed technique attains further performance enhancements by exploiting co-channel interference. The impact of the proposed technique on various modulation orders is considered in this paper. The performance is assessed through Monte Carlo simulation and accurate mathematical analysis. It will be shown that the results from both models closely match and demonstrate that significant BER reduction as well as throughput enhancement are obtained relative to other uplink OFDMA transmission techniques.

This paper proposes a new resource management (RRM) algorithm that utilizes the self-organizing network functionality for optimizing spectrum usage and minimizing co-layer interference between femtocells. To achieve this, the proposed algorithm dynamically maximizes usage of all the available subcarriers by exploiting knowledge of the users' location. Taking into account the associated overhead and power consumption it will be shown that the proposed algorithm improves the average data rate per user as well as reduced the overall system power consumption in all femtocell density scenarios, and, is also superior to existing techniques. The fact that the proposed minimizes power consumption without compromising the data rate makes it an ideal candidate for adoption in future green heterogeneous wireless networks.

This paper presents a new technique for jointly optimizing energy consumption and quality of service (QoS) in heterogeneous cellular networks employing fractional frequency reuse (FFR) in the macrocell tier. The proposed technique combines radio resource management (RRM) and network routing principles to produce an effective way of utilizing the spectrum. Based on a novel method of interference mapping, the RRM is invoked, in distributed or centralized manner, to allocate the resource. In the case of centralized RRM, network routing is applied to maximize spectrum utilization. It will be shown through matching mathematical analysis and computer simulations that, relative to existing well known techniques, the proposed technique offers significant QoS improvements, in terms of guaranteed data rate per user, as well as, enhancements in the overall energy efficiency of the network.