Heterogeneous networks are an attractive means of improving the network capacity. Heterogeneous network are typically composed of multiple radio access points (macro, pico and femto) where the base stations are transmitting with variable power. In this study, we consider the uplink of heterogeneous networks, where each terminal can simultaneously connected to multiple radio access points and requests delay-sensitive traffic (e.g., real-time video). We adopt the framework of Hou, Borkar,and Kumar, and study the delay in heterogeneous networks and analyze the multiaccess transmission delay by considering three extreme scheduling schemes. Moreover, a parallel-aggregation multiple radio access points (PA-MRA) algorithm for packet scheduling is presented to improve the transmission delay in heterogeneous networks. Analysis and numerical results show that the proposed algorithm obtains the optimal and robust transmission delay gain compared with the three extreme scheduling policies.

In this work, we study the problem of interference in a two-tiered uplink network which contains a macro-cell and multiple small-cells. We null the interference from small-cells to macro-cell by using Vandermonde-subspace frequency division multiplexing (VFDM). VFDM can exploit frequency selectivity and null space generated by the cyclic prefixes (CP) used by the macro-cell communication. We use an interference alignment (IA) scheme with an extension of a grouping method to align the interference between multiple small-cells into a lower dimensional-subspace, by using this grouping method we reduce the number of receive antennas required to null interference. Finally, we derive the achievable degrees of freedom (DoF).

In cognitive radio networks, the available spectrum holes are usually discontinuous. Hence, it is hard to exploit these spectrum holes because the bandwidth of an individual one may not be able to satisfy the wide bandwidth requirement imposed by secondary users (SUs). Spectrum aggregation (SA) enables SUs to integrate several spectrum holes into one channel with wide bandwidth which may support high bandwidth requirement. In this paper, we investigate the problem of SA based spectrum allocation. Specifically, we cast this problem into Multiple Knapsack Problems (MKP). Based on this scheme, we propose a spectrum aggregation algorithm to maximize the available bandwidth that SUs can access, as well as two spectrum allocation algorithms including an optimal algorithm and a suboptimal one. The proposed algorithms are evaluated in terms of total available bandwidth and spectrum utilization efficiency. Numerical results show that the proposed algorithms can significantly outperform the existing algorithms.

We investigate the interactive behavior and strategic decision-making between multiple secondary users (SUs) and primary users (PUs), both of which are end-to-end performance aware in cognitive networks. A Stackelberg game is utilized to formulate the spectrum utilization maximization problem after the complex interference situation is analyzed. Especially, an interference power cap (IPC) function predefined by PUs as a pricing function is introduced into the utility function design of SUs to guarantee QoS of PUs, as well as to decouple constraints. Further, an asymmetric information situation can be formed by considering PUs as leaders who employ the optimal water-filling algorithm, and the closed-form power strategy of SUs can be derived. And accordingly, SUs as followers can observe the available information to do more foresighted decision by learning. What is more, we prove the optimality and existence of the deceived solutions. Numerical results demonstrate that the proposed distributed algorithm provides more spectrum revenue and better QoS guarantees to PUs with limited iterations.

This paper investigates the multiuser interference mitigation for the uplink of an orthogonal frequency division multiple access system in a doubly selective fading channel. The proposed algorithm squeezes the interference of subcarrier k into 2τ+1 neighboring subcarriers by preprocessing the received signal and yields a banded structure interference matrix. Specifically, the value of τ mainly depends on the carrier frequency offsets and determines the squeezing depth which in turn influences the receiver implementation complexity. Simulation results show that the bit error rate performance of our proposed algorithm approaches the existing full length minimum mean square error equalizer with a significant reduction on complexity.

From an energy-saving perspective, the authors investigate the downlink power control issue of the two-tier heterogeneous networks (HetNets) using a cognitive radio train of thought. The authors consider the HetNets scenario of one macro-cell evolved-NodeB (eNB) and multiple femto-cell Home evolved NodeBs (HeNBs) cooperatively coexisting to provide better services. A specific HeNB allows macro-mobile station (macro-MS) previously associated with eNB to access to it for better signal-to-interference plus noise ratio (SINR) guarantee. As a reward, the macro-MS pays a certain of revenue to HeNB as the incentive mechanism for this HeNB's downlink extra power consumption, which is manifested in the design of the price function. The throughput bound of Macro-MSs in HeNB cell is given. Then, the authors select the SINR as the performance measure and formulate the power control of selected HeNBs as multi-constrained optimisation problem. Meanwhile, the authors derive the sub-optimal and closed-form power control of individual HeNB, based on which the authors design the distributed algorithm with the aid of eNB and HeNBs cooperatively to implement the pricing information exchange. Simulation results show the improved performance of the convergence, the energy-efficiency measured by ‘energy-per-bit’ and the throughput of the ‘Proposed-Cognitive-x’ power control algorithm.

This paper proposes a joint transmit-receive spectrum sharing method based on space division multiplexing (SDM) in cognitive radio networks (CRN). By exploiting spatial correlation features between cognitive transmission and interference from cognitive base station (CBS) to primary user (PU) as well as interference from primary base station (PBS) to cognitive user (CU), appropriate primary system and its channel are selected. Consequently spectrum sharing is carried out employing the proposed SDM based strategy. The method is a good complement for conventional cognitive radio (CR) which adopts opportunistic spectrum access. Analysis and simulation results show that compared with the method implemented only at CBS and exhaustive searching, the proposed scheme could achieve near-optimal throughput performance with reduced complexity.