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Mobile social networks have been introduced as a new efficient (i.e., minimizing bandwidth usage) and effective (i.e., minimizing the delay or maximizing the number of target recipients) way of disseminating content and information to a particular group of mobile users who share similar interests. In this paper, we investigate how the content providers and the network operator can interact to distribute content in a mobile social network. The objective of each content provider is to minimize the cost that pertains to the time used to distribute the content to the subscribed mobile users and the cost due to the price paid to the network operator for transferring the content over a wireless connection through a base station. Although the content providers can cooperate by forming coalitions for sharing a wireless connection, the network operator can control the amount of bandwidth provided over the wireless connection. We introduce a novel coalitional game model, which is referred to as the controlled coalitional game, to investigate the decision-making process of the content providers and the network operator. Numerical studies show that, given the allocated bandwidth from the network operator, the content providers can self organize into coalitions while minimizing their individual cost. In addition, the results demonstrate that the revenue of the network operator can be maximized when the bandwidth allocation is performed while considering the coalitional structure of the content providers. [ABSTRACT FROM PUBLISHER]

Collaborative spectrum sensing (CSS) between secondary users (SUs) in cognitive networks exhibits an inherent tradeoff between minimizing the probability of missing the detection of the primary user (PU) and maintaining a reasonable false alarm probability (e.g., for maintaining good spectrum utilization). In this paper, we study the impact of this tradeoff on the network structure and the cooperative incentives of the SUs that seek to cooperate to improve their detection performance. We model the CSS problem as a nontransferable coalitional game, and we propose distributed algorithms for coalition formation (CF). First, we construct a distributed CF algorithm that allows the SUs to self-organize into disjoint coalitions while accounting for the CSS tradeoff. Then, the CF algorithm is complemented with a coalitional voting game to enable distributed CF with detection probability (CF-PD) guarantees when required by the PU. The CF-PD algorithm allows the SUs to form minimal winning coalitions (MWCs), i.e., coalitions that achieve the target detection probability with minimal costs. For both algorithms, we study and prove various properties pertaining to network structure, adaptation to mobility, and stability. Simulation results show that CF reduces the average probability of miss per SU up to 88.45%, relative to the noncooperative case, while maintaining a desired false alarm. For CF-PD, the results show that up to 87.25% of the SUs achieve the required detection probability through MWCs. [ABSTRACT FROM PUBLISHER]

In this paper, we study the joint transmitter and receiver design problem over frequency-selective fading channels. Motivated by a conventional minimum mean square error decision feedback equalizer (MMSE-DFE), we present a simple approximate maximum-likelihood (ML) decision feedback equalizer at the receiver. We then perform precoding in a downlink scenario at the transmitter side to minimize the analytical symbol error rate (SER) of the proposed equalization scheme. Simulation results indicate that the proposed precoder achieves substantial performance gains over previously reported techniques. [ABSTRACT FROM AUTHOR]

This letter analyzes the performance of single relay selection cooperative wireless networks using amplify-and forward relaying. The network channels are modeled as independent, non-identical, Rician distributed coefficients. We derive approximate formulas for the symbol error rate (SER) of the opportunistic relaying cooperative network. We first derive the PDF of the approximate value of the total SNR. Then, assuming M-PSK or M-QAM modulations, the PDF is used to determine the SER. For sufficiently large SNR, this letter derives the close-form average SER. The simplicity of the asymptotic results provides valuable insights into the performance of cooperative networks and suggests means of optimizing them. We also use simulation to verify the analytical results. Results show that the derived error rates are tight bounds particularly at medium and high SNR. [ABSTRACT FROM AUTHOR]

In this paper, we propose a joint-transmitter-and-receiver design for spatial multiplexing based on a novel prewhitening detector (PWD). By using decision feedback equalization (DFE), Gaussian approximation, a prewhitening filter, and a matched filter, the proposed PWD transforms the multiple-input-multiple-output (MIMO) system into several parallel single-input-single-output (SISO) schemes and facilitates single-symbol detection. The proposed scheme achieves near-optimal symbol recovery with a complexity similar to that of a minimum-mean-square-error decision feedback equalizer (MMSE-DFE). The closed-form symbol error rate (SER) of the PWD is derived, which can be used to closely predict the ML performance for uncoded V-BLAST schemes. By assuming full channel knowledge at the transmitter side, we use a preequalizer and a precoder in a downlink scenario. The preequalizer can transfer the feedback part of the DFE to the transmitter side and thus provide better performance in a low signal-to-noise ratio (SNR) with reduced receiver complexity. The precoder designed to minimize the SER of this system can further improve performance without affecting the complexity at the receiver side. [ABSTRACT FROM AUTHOR]

In this contribution, the performance of a multiuser system is analyzed in the context of frequency selective fading channels. Using game theoretic tools, a useful framework is provided in order to determine the optimal power allocation when users know only their own channel (while perfect channel state information is assumed at the base station). This scenario illustrates the case of decentralized schemes, where limited information on the network is available at the terminal. Various receivers are considered, namely the matched filter, the MMSE filter and the optimum filter. The goal of this paper is to extend previous work, and to derive simple expressions for the non-cooperative Nash equilibrium as the number of mobiles becomes large and the spreading length increases. To that end two asymptotic methodologies are combined. The first is asymptotic random matrix theory which allows us to obtain explicit expressions of the impact of all other mobiles on any given tagged mobile. The second is the theory of non-atomic games which computes good approximations of the Nash equilibrium as the number of mobiles grows. [ABSTRACT FROM AUTHOR]

The problem of designing an optimal prefilter transform for finite impulse response (FIR) multiple-input multiple-output (MIMO) communication systems is addressed. The bit error rate (BER) is minimized under a power constraint. Binary signaling is assumed. The transmitter requires knowledge of the channel transfer function coefficients and the receiver transform. It is shown that the proposed prefiltering transform outperforms three previously known prefilter transform methods in terms of BER versus channel quality. The proposed prefilter transform is applicable to downlink communication systems where the base station can estimate the channel while receiving data from the mobile station. [ABSTRACT FROM AUTHOR]