A self-organized resource allocation scheme for heterogeneous macro-femto networks

This paper investigates the radio resource management (RRM) issues in a heterogeneous macro-femto network. The objective of femto deployment is to improve coverage, capacity, and experienced quality of service of indoor users. The location and density of user-deployed femtos is not known a-priori. This makes interference management crucial. In particular, with co-channel allocation (to improve resource utilization efficiency), RRM becomes involved because of both cross-layer and co-layer interference. In this paper, we review the resource allocation strategies available in the literature for heterogeneous macro-femto network. Then, we propose a self-organized resource allocation (SO-RA) scheme for an orthogonal frequency division multiple access based macro-femto network to mitigate co-layer interference in the downlink transmission. We compare its performance with the existing schemes like Reuse-1, adaptive frequency reuse (AFR), and AFR with power control (one of our proposed modification to AFR approach) in terms of 10 percentile user throughput and fairness to femto users. The performance of AFR with power control scheme matches closely with Reuse-1, while the SO-RA scheme achieves improved throughput and fairness performance. SO-RA scheme ensures minimum throughput guarantee to all femto users and exhibits better performance than the existing state-of-the-art resource allocation schemes

Spectral Efficiency of Multi-User Adaptive Cognitive Radio Networks

In this correspondence, the comprehensive problem of joint power, rate, and subcarrier allocation have been investigated for enhancing the spectral efficiency of multi-user orthogonal frequency-division multiple access (OFDMA) cognitive radio (CR) networks subject to satisfying total average transmission power and aggregate interference constraints. We propose novel optimal radio resource allocation (RRA) algorithms under different scenarios with deterministic and probabilistic interference violation limits based on a perfect and imperfect availability of cross-link channel state information (CSI). In particular, we propose a probabilistic approach to mitigate the total imposed interference on the primary service under imperfect cross-link CSI. A closed-form mathematical formulation of the cumulative density function (cdf) for the received signal-to-interference-plus-noise ratio (SINR) is formulated to evaluate the resultant average spectral efficiency (ASE). Dual decomposition is utilized to obtain sub-optimal solutions for the non-convex optimization problems. Through simulation results, we investigate the achievable performance and the impact of parameters uncertainty on the overall system performance. Furthermore, we present that the developed RRA algorithms can considerably improve the cognitive performance whilst abide the imposed power constraints. In particular, the performance under imperfect cross-link CSI knowledge for the proposed `probabilistic case' is compared to the conventional scenarios to show the potential gain in employing this scheme

Control and data channel resource allocation in OFDMA heterogeneous networks

This paper investigates the downlink resource allocation problem in Orthogonal Frequency Division Multiple Access (OFDMA) Heterogeneous Networks (HetNets) consisting of macro cells and small cells sharing the same frequency band. Dense deployment of small cells overlaid by a macro layer is considered to be one of the most promising solutions for providing hotspot coverage in future 5G networks. The focus is to devise an optimised policy for small cells’ access to the shared spectrum, in terms of their transmissions, in order to keep small cell served users sum data rate at high levels while ensuring that certain level of quality of service (QoS) for the macro cell users in the vicinity of small cells is provided. Both data and control channel constraints are considered, to ensure that not only the macro cell users’ data rate demands are met, but also a certain level of Bit Error Rate (BER) is ensured for the control channel information. Control channel reliability is especially important as it holds key information to successfully decode the data channel. The problem is addressed by our proposed linear binary integer programming heuristic algorithm which maximises the small cells utility while ensuring the macro users imposed constraints. To further reduce the computational complexity, we propose a progressive interference aware low complexity heuristic solution. Discussion is also presented for the implementation possibility of our proposed algorithms in a practical network. The performance of both the proposed algorithms is compared with the conventional Reuse-1 scheme under different fading conditions and small cell loads. Results show a negligible drop in small cell performance for our proposed schemes, as a trade-off for ensuring all macro users data rate demands, while Reuse-1 scheme can even lead up to 40 % outage when control region of the small cells in heavily loaded