Approximate Sum-Capacity of K-user Cognitive Interference Channels with Cumulative Message Sharing

This paper considers the K user cognitive interference channel with one primary and K-1 secondary/cognitive transmitters with a cumulative message sharing structure, i.e cognitive transmitter $i\in [2:K]$ knows non-causally all messages of the users with index less than i. We propose a computable outer bound valid for any memoryless channel. We first evaluate the sum-rate outer bound for the high- SNR linear deterministic approximation of the Gaussian noise channel. This is shown to be capacity for the 3-user channel with arbitrary channel gains and the sum-capacity for the symmetric K-user channel. Interestingly. for the K user channel having only the K th cognitive know all the other messages is sufficient to achieve capacity i.e cognition at transmitter 2 to K-1 is not needed. Next the sum capacity of the symmetric Gaussian noise channel is characterized to within a constant additive and multiplicative gap. The proposed achievable scheme for the additive gap is based on Dirty paper coding and can be thought of as a MIMO-broadcast scheme where only one encoding order is possible due to the message sharing structure. As opposed to other multiuser interference channel models, a single scheme suffices for both the weak and strong interference regimes. With this scheme the generalized degrees of freedom (gDOF) is shown to be a function of K, in contrast to the non cognitive case and the broadcast channel case. Interestingly, it is show that as the number of users grows to infinity the gDoF of the K-user cognitive interference channel with cumulative message sharing tends to the gDoF of a broadcast channel with a K-antenna transmitter and K single-antenna receivers. The analytical additive additive and multiplicative gaps are a function of the number of users. Numerical evaluations of inner and outer bounds show that the actual gap is less than the analytical one.Comment: Journa

On the Capacity of a Class of MIMO Cognitive Radios

Cognitive radios have been studied recently as a means to utilize spectrum in a more efficient manner. This paper focuses on the fundamental limits of operation of a MIMO cognitive radio network with a single licensed user and a single cognitive user. The channel setting is equivalent to an interference channel with degraded message sets (with the cognitive user having access to the licensed user's message). An achievable region and an outer bound is derived for such a network setting. It is shown that under certain conditions, the achievable region is optimal for a portion of the capacity region that includes sum capacity.Comment: 13 pages, 8 figures, Accepted for publication in Journal of Selected Topics in Signal Processing (JSTSP) - Special Issue on Dynamic Spectrum Acces

Interference Alignment in Multi-Input Multi-Output Cognitive Radio-Based Network

This study investigates the interference alignment techniques for cognitive radio networks toward 5G to meet the demand and challenges for future wireless communications requirements. In this context, we examine the performance of the interference alignment in two parts. In the first part of this chapter, a multi-input multi-output (MIMO) cognitive radio network in the presence of multiple secondary users (SUs) is investigated. The proposed model assumes that linear interference alignment is used at the primary system to lessen the interference between primary and secondary networks. Herein, we derive the closed-form mathematical equations for the outage probability considering the interference leakage occurred in the primary system. The second part of this study analyzes the performance of interference alignment for underlay cognitive two-way relay networks with channel state information (CSI) quantization error. Here, a two-way amplify-and-forward relaying scheme is considered for independent and identically distributed Rayleigh fading channel. The closed-form average pairwise error probability expressions are derived, and the effect of CSI quantization error is analyzed based on the bit error rate performance. Finally, we evaluate the instantaneous capacity for both primary and secondary networks*

Interference Alignment and the Degrees of Freedom for the K User Interference Channel

While the best known outerbound for the K user interference channel states that there cannot be more than K/2 degrees of freedom, it has been conjectured that in general the constant interference channel with any number of users has only one degree of freedom. In this paper, we explore the spatial degrees of freedom per orthogonal time and frequency dimension for the K user wireless interference channel where the channel coefficients take distinct values across frequency slots but are fixed in time. We answer five closely related questions. First, we show that K/2 degrees of freedom can be achieved by channel design, i.e. if the nodes are allowed to choose the best constant, finite and nonzero channel coefficient values. Second, we show that if channel coefficients can not be controlled by the nodes but are selected by nature, i.e., randomly drawn from a continuous distribution, the total number of spatial degrees of freedom for the K user interference channel is almost surely K/2 per orthogonal time and frequency dimension. Thus, only half the spatial degrees of freedom are lost due to distributed processing of transmitted and received signals on the interference channel. Third, we show that interference alignment and zero forcing suffice to achieve all the degrees of freedom in all cases. Fourth, we show that the degrees of freedom $D$ directly lead to an $\mathcal{O}(1)$ capacity characterization of the form $C(SNR)=D\log(1+SNR)+\mathcal{O}(1)$ for the multiple access channel, the broadcast channel, the 2 user interference channel, the 2 user MIMO X channel and the 3 user interference channel with M>1 antennas at each node. Fifth, we characterize the degree of freedom benefits from cognitive sharing of messages on the 3 user interference channel.Comment: 30 pages. Revision extends the 3 user proof to K user