Achievable regions for interference channels with generalized and intermittent feedback

In this paper, we have combined a game‐theoretic and an information‐theoretic notions to describe the selfish behavior of each user in a two‐user linear deterministic cognitive interference channel (LD‐CIC). The two‐user LD‐CIC is the simple case of the cognitive radio technology in the high SNR regime. This model is a solution to improve the spectral efficiency in software defined network (SDN) concept in 5G. In the two‐user LD‐CIC, the information bits of the primary/licensed transmitter is a‐priori provided at the cognitive/secondary/unlicensed transmitter. So that, the cognitive transmitter can cooperate and utilize the frequency spectrum to send the information bits of the both transmitters. In information‐theoretic approaches, full cooperation is assumed between transmitters for codebook and rate selection in this channel. This may not be a realistic assumption if transmitters are selfish and are willing to maximize their own benefit. In particular, we have defined the Stackelberg equilibrium (SE) region on the capacity region of the two‐user LD‐CIC to capture the behavior of each transmitter when they compete even though one of them is informed of the other transmitter information bits. We have implemented a two‐phase Stackelberg game with the primary and cognitive transmitters acting as the leader in the first phase, and the follower in the second phase, respectively. In this implementation, both transmitters are assumed to be selfish and only interested in optimizing their own pay‐offs. The SE region is characterized as a subset of capacity region in which the transmitters cannot gain more transmission rate by individually deviating from the SE strategy. The achievability of the resultant region has been configured using a randomized Han‐Kobayashi scheme for all the channel gains. Also, we have compared the obtained SE region with the previous equilibrium regions such as Nash equilibrium (NE) region of the linear deterministic interference channel (LD‐IC). The results have shown that the SE points on the sum‐rate of the LD‐CIC capacity region are more than the NE points on the sum rate of the capacity region of LD‐IC, so the SE region of the LD‐CIC is Pareto superior to the NE region of LD‐IC.

This work proposes a new coding scheme for the discrete memoryless two-user interference channel whose receivers can cooperate to decode their desired messages. The coding scheme is built upon Han-Kobayashi rate splitting and superposition coding at the transmitters, noisy network coding, and non-unique joint decoding at the receivers. As a case study the general achievable region leads to an inner bound for the Gaussian interference channel whose receivers cooperate through rate-limited orthogonal channels. It is shown that this inner bound is equivalent to the one-round quantize-bin-and-forward inner bound established by Wang and Tse, thereby showing that noisy network coding achieves within 1 bit/s/Hz to the capacity region when the interference is strong, and achieves within 1 bit/s/Hz to the capacity region of the Gaussian compound multiple access channel with conferencing decoders regardless of channel parameters.

We investigate how to exploit intermittent feedback for interference management. Focusing on the two-user linear deterministic interference channel, we completely characterize the capacity region. We find that the characterization only depends on the forward channel parameters and the marginal probability distribution of each feedback link. The scheme we propose makes use of block Markov encoding and quantize-map-and-forward at the transmitters, and backward decoding at the receivers. Matching outer bounds are derived based on novel genie-aided techniques. As a consequence, the perfect-feedback capacity can be achieved once the two feedback links are active with large enough probabilities.

The N +1 user, 1 ×N single-input multiple-output (SIMO) Gaussian interference channel where each transmitter has a single antenna and each receiver has N antennas is studied. The sum capacity within O(1) is characterized for the symmetric case where all direct links have the same signal-to-noise ratio (SNR) and all undesired links have the same interference-to-noise ratio (INR). The gap to the exact capacity is a constant which is independent of SNR and INR. To get this result, we first generalize the deterministic interference channel introduced by El Gamal and Costa to model interference channels with multiple antennas. We derive the capacity region of this deterministic interference channel. Based on the insights provided by the deterministic channel, we characterize the generalized degrees of freedom (GDOF) of Gaussian case, which directly leads to the O(1) capacity approximation. On the achievability side, an interesting conclusion is that the GDOF regime where treating interference as noise is found to be optimal in the two-user interference channel, does not appear in the N + 1 user, 1 × N SIMO case. On the converse side, new multiuser outer bounds emerge out of this work that do not follow directly from the two-user case. In addition to the GDOF region, the outer bounds identify a strong interference regime where the capacity region is established.

Uplink and downlink cloud radio access networks are modeled as two-hop ${K}$ -user ${L}$ -relay networks, whereby small base-stations act as relays for end-to-end communications and are connected to a central processor via orthogonal fronthaul links of finite capacities. Simplified versions of network compress–forward (or noisy network coding) and distributed decode–forward are presented to establish inner bounds on the capacity region for uplink and downlink communications, that match the respective cutset bounds to within a finite gap independent of the channel gains and signal to noise ratios. These approximate capacity regions are then compared with the capacity regions for networks with no capacity limit on the fronthaul. Although it takes infinite fronthaul link capacities to achieve these “fronthaul-unlimited” capacity regions exactly, these capacity regions can be approached approximately with finite-capacity fronthaul. The total fronthaul link capacities required to approach the fronthaul-unlimited sum-rates (for uplink and downlink) are characterized. Based on these results, the capacity scaling law in the large network size limit is established under certain uplink and downlink network models, both theoretically and via simulations.

We propose two coding schemes combining decode-forward (DF) and noisy network coding (NNC) with different flavors. The first is a combined DF-NNC scheme for the oneway relay channel which includes both DF and NNC as special cases by performing rate splitting, partial block Markov encoding and NNC. The second combines two different DF strategies and layered NNC for the two-way relay channel. One DF strategy performs coherent block Markov encoding at the source at the cost of power splitting at the relay, the other performs independent source and relay encoding but with full relay power, and layered NNC allows a different compression rate for each destination. Analysis and simulation show that both proposed schemes supersede each individual scheme and take full advantage of both DF and NNC.

This paper revisits the interference channels under strong interference and very strong interference, for both discrete memoryless and Gaussian channels. In particular, it is shown that for the classical definitions, while the conditions of strong interference for discrete and Gaussian cases coincide with each other, those of very strong interference are not consistent with each other in terms of mutual information inequalities. Based on this observation, a new class of discrete memoryless interference channels under very strong interference is introduced whose capacity region is characterized. This new class of channels is consistent with the Gaussian interference channel under very strong interference. Moreover, this new class of interference channels is not a subset of any existing classes of discrete memoryless interference channels with known capacity region.

With the advent of sensor nodes with higher communication and sensing capabilities, the challenge arises in forming a data gathering network to maximize the network capacity. The channel sharing for higher data transmission leads to interfering problems. The effects of interferences become increasingly important when simultaneous transmissions are done in order to increase wireless network capacity. In such cases, achieving a high throughput and low delay is difficult. We propose a new method that uses interference alignment (IA) technique to mitigate interference effects in Wireless Sensor Networks (WSNs). In IA technique, multiple transmitters jointly encode their signals to intended receivers such that interfering signals are separated and eliminated. Simulation results demonstrate that compared to TDMA algorithms, the proposed method significantly increases the performance of the network delay and throughput by reducing the delay and increasing throughput.

This work presents novel achievable schemes for the 2-user symmetric linear deterministic interference channel with limited-rate transmitter cooperation and perfect secrecy constraints at the receivers. The proposed achievable scheme consists of a combination of interference cancelation, relaying of the other user's data bits, time sharing, and transmission of random bits, depending on the rate of the cooperative link and the relative strengths of the signal and the interference. The results show, for example, that the proposed scheme achieves the same rate as the capacity without the secrecy constraints, in the initial part of the weak interference regime. Also, sharing random bits through the cooperative link can achieve a higher secrecy rate compared to sharing data bits, in the very high interference regime. The results highlight the importance of limited transmitter cooperation in facilitating secure communications over 2-user interference channels.

Deterministic channel models have recently proven to be powerful tools for obtaining capacity bounds for Gaussian multiuser networks that are tight in the high SNR regime. In this work we apply this technique to the Gaussian cognitive radio channel: a 2×2 interference channel in which one transmitter has non-causal knowledge of the message of the other, whose capacity region in general is unknown. We approximate the Gaussian cognitive radio channel at high SNR by an underlying binary linear deterministic channel model for which we determine the exact capacity region.

We provide a natural formulation of information theoretic games on interference channels. We analyze this game on a class of deterministic interference channels recently introduced to approximate Gaussian channels in the interference-limited regime. Our main result is a complete and simple characterization of the subset of the interference channel capacity region that can be achieved as Nash equilibria. We show that for all parameter values of the interference channel, there are always Nash equilibria which are efficient, i.e. on the boundary of the capacity region.

For noisy network with multiple relays, short message noisy network coding with rate splitting (SNNC-RS) scheme is presented. It has recently been shown by Hou and Kramer that mixed cooperative strategies in which relays in favorable positions decode-and-forward (DF) and the rest quantize via short message noisy network coding (SNNC) can outperform existing cooperative strategies (e.g., noisy network coding (NNC) and decode-and-forward). A drawback of such schemes is that forwarding of quantized signals at SNNC relays introduces interference to the rest of the relays. Our proposed relaying scheme has a capability to reduce such interference and thereby improve the rate performance. In the proposed scheme, superposition coding is incorporated into SNNC encoding to enable partial interference cancellation at DF relays. The achievable rate with proposed scheme is derived for the discrete two-relay network and evaluated in the Gaussian case where gains over the rate achievable without rate splitting are demonstrated.

In this paper we study interference management in wireless networks with bursty user traffic. In each time slot, whether a user is on or off for transmission is governed by its own Bernoulli random state. At each transmitter, the states of activities of other users are only available via feedback. We investigate a canonical two-user bursty Gaussian interference channel (IC) with three different feedback models: (1) no feedback, (2) delayed state feedback, and (3) channel output feedback. In all three cases, we characterize the capacity region of the bursty Gaussian IC to within a bounded gap. It turns out that the near-optimal transmit strategies in the non-bursty IC suffice to establish the approximate characterization of capacity in all three cases. In other words, traffic burstiness does not change the high-SNR optimality of the schemes as long as receivers keep track of user activities. Moreover, the capacity region with delayed state feedback is within a bounded gap to that without feedback, and therefore delayed state feedback does not provide significant improvement at high SNR.

A Kt χ Kr cache-aided wireless interference network, in which both the transmitters and the receivers are equipped with cache memories is studied. Each user requests one file from a library of N popular files. The goal is to design the cache contents without the knowledge of the particular user demands, such that all possible demand combinations can be satisfied reliably over the interference channel. The achievable sum degrees-of-freedom (sDoF) and the normalized delivery time (NDT) are studied for centralized and decentralized network architectures, respectively. First, using a combination of interference alignment (IA), zero-forcing (ZF) and interference cancellation (IC) techniques, a novel caching and transmission scheme for centralized networks is introduced, and it is shown to improve the sDoF upon the state-of-the-art. Then, the NDT is studied when the content placement at the receiver caches is carried out in a decentralized manner. Our results indicate that, for this particular network architecture, caches located at the receiver side are more effective than those at the transmitter side in order to reduce the NDT.

This paper studies the capacity of a class of discrete memoryless interference channels (DMICs), where interference is defined analogous to that of a Gaussian interference channel with one-sided weak interference. The sum-rate capacity of this class of channels is determined. As with the Gaussian case, the sum-rate capacity is achieved by letting the transceiver pair subject to interference communicate at a rate such that its message can be decoded at the unintended receiver using single user detection. It is also established that this class of DMICs is equivalent in capacity region to certain degraded interference channels. This allows the construction of capacity outer-bounds using the capacity regions of associated degraded broadcast channels. The same technique is then used to determine the sum-rate capacity of DMICs with mixed interference as defined in this paper. The obtained capacity bounds and sum-rate capacities are used to resolve the capacities of several new DMICs.