Impact of Channel Estimation Errors on Multiuser Detection via the Replica Method

For practical wireless DS-CDMA systems, channel estimation is imperfect due to noise and interference. In this paper, the impact of channel estimation errors on multiuser detection (MUD) is analyzed under the framework of the replica method. System performance is obtained in the large system limit for optimal MUD, linear MUD and turbo MUD, and is validated by numerical results for finite systems.Comment: To appear in the EURASIP Journal on Wireless Communication and Networking - Special Issue on Advanced Signal Processing Algorithms for Wireless Communication

Large System Analysis of Game-Theoretic Power Control in UWB Wireless Networks with Rake Receivers

This paper studies the performance of partial-Rake (PRake) receivers in impulse-radio ultrawideband wireless networks when an energy-efficient power control scheme is adopted. Due to the large bandwidth of the system, the multipath channel is assumed to be frequency-selective. By using noncooperative game-theoretic models and large system analysis, explicit expressions are derived in terms of network parameters to measure the effects of self- and multiple-access interference at a receiving access point. Performance of the PRake is compared in terms of achieved utilities and loss to that of the all-Rake receiver.Comment: To appear in the Proceedings of the 8th IEEE International Workshop on Signal Processing Advances in Wireless Communications (SPAWC), Helsinki, Finland, June 17-20, 200

Cooperative Non-Orthogonal Multiple Access in 5G Systems

Non-orthogonal multiple access (NOMA) has recently received considerable attention as a promising candidate for 5G systems. A key feature of NOMA is that users with better channel conditions have prior information about the messages of the other users. This prior knowledge is fully exploited in this paper, where a cooperative NOMA scheme is proposed. Outage probability and diversity order achieved by this cooperative NOMA scheme are analyzed, and an approach based on user pairing is also proposed to reduce system complexity in practice

Packet Relaying Control in Sensing-based Spectrum Sharing Systems

Cognitive relaying has been introduced for opportunistic spectrum access systems by which a secondary node forwards primary packets whenever the primary link faces an outage condition. For spectrum sharing systems, cognitive relaying is parametrized by an interference power constraint level imposed on the transmit power of the secondary user. For sensing-based spectrum sharing, the probability of detection is also involved in packet relaying control. This paper considers the choice of these two parameters so as to maximize the secondary nodes' throughput under certain constraints. The analysis leads to a Markov decision process using dynamic programming approach. The problem is solved using value iteration. Finally, the structural properties of the resulting optimal control are highlighted

Adaptive Modulation in Multi-user Cognitive Radio Networks over Fading Channels

In this paper, the performance of adaptive modulation in multi-user cognitive radio networks over fading channels is analyzed. Multi-user diversity is considered for opportunistic user selection among multiple secondary users. The analysis is obtained for Nakagami-$m$ fading channels. Both adaptive continuous rate and adaptive discrete rate schemes are analysed in opportunistic spectrum access and spectrum sharing. Numerical results are obtained and depicted to quantify the effects of multi-user fading environments on adaptive modulation operating in cognitive radio networks

Fronthaul-Constrained Cloud Radio Access Networks: Insights and Challenges

As a promising paradigm for fifth generation (5G) wireless communication systems, cloud radio access networks (C-RANs) have been shown to reduce both capital and operating expenditures, as well as to provide high spectral efficiency (SE) and energy efficiency (EE). The fronthaul in such networks, defined as the transmission link between a baseband unit (BBU) and a remote radio head (RRH), requires high capacity, but is often constrained. This article comprehensively surveys recent advances in fronthaul-constrained C-RANs, including system architectures and key techniques. In particular, key techniques for alleviating the impact of constrained fronthaul on SE/EE and quality of service for users, including compression and quantization, large-scale coordinated processing and clustering, and resource allocation optimization, are discussed. Open issues in terms of software-defined networking, network function virtualization, and partial centralization are also identified.Comment: 5 Figures, accepted by IEEE Wireless Communications. arXiv admin note: text overlap with arXiv:1407.3855 by other author

Measurement Matrix Design for Compressive Sensing Based MIMO Radar

In colocated multiple-input multiple-output (MIMO) radar using compressive sensing (CS), a receive node compresses its received signal via a linear transformation, referred to as measurement matrix. The samples are subsequently forwarded to a fusion center, where an L1-optimization problem is formulated and solved for target information. CS-based MIMO radar exploits the target sparsity in the angle-Doppler-range space and thus achieves the high localization performance of traditional MIMO radar but with many fewer measurements. The measurement matrix is vital for CS recovery performance. This paper considers the design of measurement matrices that achieve an optimality criterion that depends on the coherence of the sensing matrix (CSM) and/or signal-to-interference ratio (SIR). The first approach minimizes a performance penalty that is a linear combination of CSM and the inverse SIR. The second one imposes a structure on the measurement matrix and determines the parameters involved so that the SIR is enhanced. Depending on the transmit waveforms, the second approach can significantly improve SIR, while maintaining CSM comparable to that of the Gaussian random measurement matrix (GRMM). Simulations indicate that the proposed measurement matrices can improve detection accuracy as compared to a GRMM