A Study of Trade-off between Opportunistic Resource Allocation and Interference Alignment in Femtocell Scenarios

One of the main problems in wireless heterogeneous networks is interference between macro- and femto-cells. Using Orthogonal Frequency-Division Multiple Access (OFDMA) to create multiple frequency orthogonal sub-channels, this interference can be completely avoided if each sub-channel is exclusively used by either macro- or a femto-cell. However, such an orthogonal allocation may be inefficient. We consider two alternative strategies for interference management, opportunistic resource allocation (ORA) and interference alignment (IA). Both of them utilize the fading fluctuations across frequency channels in different ways. ORA allows the users to interfere, but selecting the channels where the interference is faded, while the desired signal has a good channel. IA uses precoding to create interference-free transmissions; however, such a precoding changes the diversity picture of the communication resources. In this letter we investigate the interactions and the trade-offs between these two strategies.Comment: This paper is submitted to IEEE Wireless Communications Letter

Beamforming and Rate Allocation in MISO Cognitive Radio Networks

We consider decentralized multi-antenna cognitive radio networks where secondary (cognitive) users are granted simultaneous spectrum access along with license-holding (primary) users. We treat the problem of distributed beamforming and rate allocation for the secondary users such that the minimum weighted secondary rate is maximized. Such an optimization is subject to (1) a limited weighted sum-power budget for the secondary users and (2) guaranteed protection for the primary users in the sense that the interference level imposed on each primary receiver does not exceed a specified level. Based on the decoding method deployed by the secondary receivers, we consider three scenarios for solving this problem. In the first scenario each secondary receiver decodes only its designated transmitter while suppressing the rest as Gaussian interferers (single-user decoding). In the second case each secondary receiver employs the maximum likelihood decoder (MLD) to jointly decode all secondary transmissions, and in the third one each secondary receiver uses the unconstrained group decoder (UGD). By deploying the UGD, each secondary user is allowed to decode any arbitrary subset of users (which contains its designated user) after suppressing or canceling the remaining users.Comment: 32 pages, 6 figure

Rate allocation in multiuser cognitive radio systems with successive group decoding

We consider the problem of rate allocation in classical as well as generalized multiuser cognitive radio systems. Each user intends to communicate with its designated receiver and all receivers employ successive group decoders with specified complexity constraints. Rate allocations in the classical case are obtained by using algorithms designed for a user Gaussian Interference Channel (GIC). In the generalized cognitive radio system the transmission rates of the primary users are assumed to be pre-determined such that each primary user is decodable at its (primary) receiver in the GIC consisting only of the primary transmitter-receiver pairs. We investigate the problem of selecting an active set of secondary users that are allowed to co-exist with the primary users and allocating rates to them under the constraints that each primary user achieves its pre-determined rate and no primary receiver decodes any secondary user. Each secondary receiver however is free to decode any other user whose codebook it is aware of. The key feature of the rate allocation algorithms we design is that inspite of using distributed and low-complexity “greedy” sub-routines, they can achieve globally optimal solutions

Distributed Beamforming and Rate Allocation in Multi-Antenna Cognitive Radio Networks

Abstract—We consider decentralized multi-antenna cognitive radio networks where secondary (cognitive) users are granted simultaneous spectrum access along with license-holding (pri-mary) users. We investigate the problem of designing beam-formers for the secondary users by maximizing the minimum rate, subject to a limited sum-power budget and constraints on the interference level imposed on each primary receiver. We consider two scenarios: the first one allows only single-user decoding at each secondary receiver whereas in the second case each secondary receiver is allowed to employ advanced multi-user decoding and is free to decode any subset of secondary users. We provide an optimal distributed algorithm for the first scenario and an explicit formulation of the optimization problem corresponding to the second scenario. This problem however is non-convex and hence cannot be efficiently solved even in a centralized setup. As a remedy, we suggest a two-step approach. In particular, the beamformers are first designed assuming single user decoding at each secondary receiver. An optimal distributed low-complexity algorithm is then proposed to allocate excess rates to the secondary users, which are made possible due to the use of advanced decoders at the secondary receivers. Simulation results demonstrate the gains yielded by the optimal beamformers as well as the rate allocation algorithms. I