ترغب بنشر مسار تعليمي؟ اضغط هنا

Prioritized Random MAC Optimization via Graph-based Analysis

216   0   0.0 ( 0 )
 نشر من قبل Laura Toni
 تاريخ النشر 2015
  مجال البحث الهندسة المعلوماتية
والبحث باللغة English




اسأل ChatGPT حول البحث

Motivated by the analogy between successive interference cancellation and iterative belief-propagation on erasure channels, irregular repetition slotted ALOHA (IRSA) strategies have received a lot of attention in the design of medium access control protocols. The IRSA schemes have been mostly analyzed for theoretical scenarios for homogenous sources, where they are shown to substantially improve the system performance compared to classical slotted ALOHA protocols. In this work, we consider generic systems where sources in different importance classes compete for a common channel. We propose a new prioritized IRSA algorithm and derive the probability to correctly resolve collisions for data from each source class. We then make use of our theoretical analysis to formulate a new optimization problem for selecting the transmission strategies of heterogenous sources. We optimize both the replication probability per class and the source rate per class, in such a way that the overall system utility is maximized. We then propose a heuristic-based algorithm for the selection of the transmission strategy, which is built on intrinsic characteristics of the iterative decoding methods adopted for recovering from collisions. Experimental results validate the accuracy of the theoretical study and show the gain of well-chosen prioritized transmission strategies for transmission of data from heterogenous classes over shared wireless channels.

قيم البحث

اقرأ أيضاً

We propose an improvement of the random spreading approach with polar codes for unsourced multiple access. Each user encodes its message by a polar code, and the coded bits are then spread using a random spreading sequence. The proposed approach divi des the active users into different groups, and employs different power levels for each group in such a way that the average power constraint is satisfied. We formulate and solve an optimization problem to determine the number of groups, and the number of users and power level of each group. Extensive simulations show that the proposed approach outperforms the existing methods, especially when the number of active users is large.
A low-density parity-check (LDPC) code is a linear block code described by a sparse parity-check matrix, which can be efficiently represented by a bipartite Tanner graph. The standard iterative decoding algorithm, known as belief propagation, passes messages along the edges of this Tanner graph. Density evolution is an efficient method to analyze the performance of the belief propagation decoding algorithm for a particular LDPC code ensemble, enabling the determination of a decoding threshold. The basic problem addressed in this work is how to optimize the Tanner graph so that the decoding threshold is as large as possible. We introduce a new code optimization technique which involves the search space range which can be thought of as minimizing randomness in differential evolution or limiting the search range in exhaustive search. This technique is applied to the design of good irregular LDPC codes and multiedge type LDPC codes.
We take two new approaches to design efficient algorithms for transmitter optimization under rate constraints, to guarantee the Quality of Service in general MIMO interference networks, which is a combination of multiple interfering broadcast channel s (BC) and multiaccess channels (MAC) and is named B-MAC Networks. Two related optimization problems, maximizing the minimum of weighted rates under a sum-power constraint and minimizing the sum-power under rate constraints, are considered. The first approach takes advantage of existing efficient algorithms for SINR problems by building a bridge between rate and SINR through the design of optimal mappings between them. The approach can be applied to other optimization problems as well. The second approach employs polite water-filling, which is the optimal network version of water-filling that we recently found. It replaces most generic optimization algorithms currently used for networks and reduces the complexity while demonstrating superior performance even in non-convex cases. Both centralized and distributed algorithms are designed and the performance is analyzed in addition to numeric examples.
Recently, the spatial modulation (SM) technique has been proposed for visible light communication (VLC). This paper investigates the average symbol error rate (SER) for the VLC using adaptive spatial modulation (ASM). In the system, the analysis of t he average SER is divided into two aspects: the error probability of the spatial domain and the error probability of the signal domain when the spatial domain is correctly estimated. Based on the two aspects, the theoretical expression of the average SER is derived. To further improve the system performance, an optimization problem is proposed to optimize the modulation orders on the LEDs. The ASM based and the candidate reduction (CR)-ASM based optimization algorithms are proposed to solve the problem, respectively. Numerical results show that the derived theoretical values of the average SER are quite accurate to evaluate the system performance. Moreover, compared with the existing schemes, the proposed two algorithms are better choices for VLC.
Relay-assisted free-space optical (FSO) communication systems are exploited as a means to mitigate the limiting effects of the turbulence induced atmospheric scintillation. However, conventional ground relays are stationary, and their optimal placeme nt is not always feasible. Due to their mobility and flexibility, unmanned aerial vehicles (UAVs) provide new opportunities for FSO relaying systems. In this paper, a hovering UAV-based serial FSO decode-and-forward relaying system is investigated. In the channel modelling for such a system, four types of impairments (i.e., atmospheric loss, atmospheric turbulence, pointing error, and link interruption due to angle-of-arrival fluctuation) are considered. Based on the proposed channel model, a tractable expression for the probability density function of the total channel gain is obtained. Closed-form expressions of the link outage probability and end-to-end outage probability are derived. Asymptotic outage performance bounds for each link and the overall system are also presented to reveal insights into the impacts of different impairments. To improve system performance, we optimize the beam width, field-of-view and UAVs locations. Numerical results show that the derived theoretical expressions are accurate to evaluate the outage performance of the system. Moreover, the proposed optimization schemes are efficient and can improve performance significantly.
التعليقات
جاري جلب التعليقات جاري جلب التعليقات
سجل دخول لتتمكن من متابعة معايير البحث التي قمت باختيارها
mircosoft-partner

هل ترغب بارسال اشعارات عن اخر التحديثات في شمرا-اكاديميا