Kai Niu

Performance of Dual-Hop Transmissions with Fixed Gain Relays over Generalized-K Fading Channels

We present the end-to-end performance of dual-hop wireless communication systems with non-regenerative fixed gain relays operating over independent not necessarily identically Generalized-K (KG) fading channels. New closed-form expressions are derived for the moments of the end-to-end signal-to-noise ratio (SNR), while the corresponding moment-generating function (MGF) is accurately approximated with the aid of Pade approximants theory. Useful performance criteria are studied; the average end-to-end SNR and the amount of fading, which are expressed in closed form, the average bit-error probability for several coherent, noncoherent, and multilevel modulation schemes, and the outage probability, which are both accurately approximated using the well-known MGF approach. Furthermore, novel closed-form expression is obtained for the gain of semi-blind relays over KG fading channels. The proposed mathematical analysis is complemented by various performance evaluation results, which demonstrate the accuracy of the theoretical approach.

Practical polar code construction over parallel channels

Channel polarisation results are extended to the case of communications over parallel channels, where the channel state information is known to both the encoder and decoder. Given a set of parallel binary-input discrete memoryless channels (B-DMCs), by performing the channel polarising transformation over independent copies of these component channels, we obtain a second set of synthesised binary-input channels. Similar to the single-channel case, we prove that as the size of the transformation goes infinity, some of the resulting channels tend to completely noised, and the others tend to noise-free, where the fraction of the latter approaches the average symmetric capacity of the underlying component channels. For finite-length polar coding over parallel channels, performance is found to be relied heavily on the specific channelmapping scheme. To avoid exhaustive searching, an empirically good scheme that is called equal-capacity partition channel mapping is proposed and numerical results show that the proposed scheme significantly outperforms random mapping. Further, utilising the above results, a polar coding method for arbitrary code length is proposed, which has potential applications in practical systems.

A novel OFDM channel estimation method based on Kalman filtering and distributed compressed sensing

Channel estimation is important for coherent detection in orthogonal frequency-division multiplexing (OFDM) systems. Current frequency-domain Kalman filtering (FDKF) channel tracking method requires a large number of pilots, which reduces the spectral efficiency of the system and increases the complexity. In this paper, in order to solve this problem, a new channel estimation method based on the recent methodology of distributed compressed sensing (DCS) and FDKF is proposed. By exploiting the sparse attribute of OFDM channels and introducing DCS, the number of pilots could be reduced greatly, which means more resources are saved for data transmission. Moreover, simulations indicate the proposed method achieves a better performance than conventional FDKF and least square (LS) method.

Performance Analysis of Cooperative ARQ with Code Combining over Nakagami-m Fading Channels

This paper presents the performance of cooperative ARQ schemes in Nakagami-m fading networks, where coherent equal gain code combining is adopted to combine the retransmitted signals at the destination. Two different retransmission protocols are adopted upon the reception failure of the destination. Once the relay node can decode correctly, the retransmission will be performed by relay in protocol I or the better node between source and relay in protocol II, where the better means having a better channel to the destination. By approximating the product of two independent Nakagami-m random variables to the sum of two independent gamma random variables, the performance of protocol I is derived at high signal-to-noise ratio (SNR). We further develop the approximation for the product of two maximum Nakagami-m random variables, which is employed to obtain the performance of protocol II at high SNR. The reliability of theoretical analysis is validated by simulation results, where the advantages of these two protocols upon the conventional protocols are presented.

Channel estimation based on distributed compressed sensing in amplify-and-forward relay networks

Abstract In orthogonal frequency-division multiplexing (OFDM) amplify-and-forward (AF) relay networks, in order to exploit diversity gains over frequency-selective fading channels, the receiver needs to acquire the knowledge of channel state information (CSI). In this article, based on the recent methodology of distributed compressed sensing (DCS), a novel channel estimation scheme is proposed. The joint sparsity model 2 (JSM-2) in DCS theory and simultaneous orthogonal matching pursuit (SOMP) are both introduced to improve the estimation performance and increase the spectral efficiency. Simulation results show that compared with current compressed sensing (CS) methods, the estimation error of our scheme is reduced dramatically in high SNR region while the pilot number is still kept small.

Connectivity of interference limited cognitive radio networks

This paper considers the connectivity of cognitive radio networks, which is defined as the existence of an infinite connected component of secondary users. The connectivity reveals the possibility of communication between an arbitrary pair of nodes in the secondary network, while long range communication is achieved in a multi-hop fashion. In their seminal work, Wei Ren et al. introduce the concept of connectivity region, and characterize some basic properties based on the Poisson Boolean model. In this paper, we take interference into consideration and study the impact of interference to the connectivity of the secondary network. Using methodologies of stochastic geometry and percolation theory, we find that the connectivity region without taking interference into consideration is a subset of our connectivity region, which means interference will not adversely affect the connectivity of secondary network. Specifically, as long as the density pair of the two networks lies in the connectivity region established in the Poisson boolean model, there must exist an orthogonal factor γ which guarantees the connectivity of the interference limited secondary network.

Coverage and capacity optimization in LTE network based on non-cooperative games

Abstract As to provide the optimal coverage and capacity performance, support high-data-rate service and decrease the capital expenditures and operational expenditures (OPEX) (CAPEX) for operator, the coverage and capacity optimization (CCO) is one of the key use cases in long term evolution (LTE) self-organization network (SON). In LTE system, some factors (e.g. load, traffic type, user distribution, uplink power setting, inter-cell interference, etc.) limit the coverage and capacity performance. From the view of single cell, it always pursuits maximize performance of coverage and capacity by optimizing the uplink power setting and intra-cell resource allocation, but it may result in decreasing the performance of its neighbor cells. Therefore, the benefit of every cell conflicts each other. In order to tradeoff the benefit of every cell and maximize the performance of the whole network, this paper proposes a multi-cell uplink power allocation scheme based on non-cooperative games. The scheme aims to make the performance of coverage and capacity balanced by the negotiation of the uplink power parameters among multi-cells. So the performance of every cell can reach the Nash equilibrium, making it feasible to reduce the inter-cell interference by setting an appropriate uplink power parameter. Finally, the simulation result shows the proposed algorithm can effectively enhance the performance of coverage and capacity in LTE network.

Sub-Sampling Framework of Distributed Video Coding

Distributed video coding (DVC) has recently been proposed to reduce the complexity of the encoder, whereas it suffers from the sampling cost of huge amount of image data. To relax such sampling burden, this paper develops a novel sub-sampling distributed video coding (SuDVC) by utilizing compressive sensing (CS) technique. Due to the inherent sparsity in video sources, the video frames are compressively sampled at the encoder. On the other hand, by exploiting the correlation between CS measurements and side information and by performing sparsity recovery, the video frames are recovered at the decoder. When compared with the traditional fully-sampling equivalence, SuDVC enjoys the reduction of transmission rate, the reduction of implementation complexity and the robustness to channel losses, which are verified in the simulations.

End-to-end utility-based resource allocation for multi-RAT nodes in heterogeneous cognitive wireless networks

Abstract This paper studies the problem of effective resource allocation for multi-radio access technologies (Multi-RAT) nodes in heterogeneous cognitive wireless networks (HCWNs). End-to-end utility, which is defined as the delay of end-to-end communication, is taken into account in this paper. In the scenario of HCWNs, it is assumed that the cognitive radio nodes have the ability of Multi-RAT and can communicate with each other through different paths simultaneously by splitting the arrival packets. In this paper, the problem is formulated as the optimization of split ratio and power allocation of the source cognitive radio node to minimize the delay of end-to-end communication, and a low complexity step-by-step iterative algorithm is proposed. Numerical results show good performance of the proposed algorithm over two other conventional algorithms.

Transmission capacity of secondary networks in hybrid overlaid/underlaid cognitive radio systems

We study the transmission capacity of the secondary (SR) network in the hybrid cognitive radio (CR) system where underlaid and overlaid access approaches are combined to improve the transmission capacity of the SR network. The transmission behavior of the primary (PR) network is characterized as a two-state (idle and busy) discrete time Markov model, and sensing performance of the SR network captured by the missed detection probability and false alarm probability is also considered. We analyze their effects on the transmission capacity of the SR network and the outage probability of the PR network. Analysis and numeric results show that hybrid mode has greater superiority than either overlaid mode or underlaid mode on the transmission capacity of the SR network, especially when the PR network has light load. The missed detection has good effect on the transmission capacity of the SR network, but increases the outage probability of the PR network, which is dispointed. The false alarm has no effect on the outage probability of the PR network, but decreases the transmission capacity of the SR network.