Applications of Soft Computing in Mobile and Wireless Communications

Soft computing is a synergistic combination of artificial intelligence methodologies to model and solve real world problems that are either impossible or too difficult to model mathematically. Furthermore, the use of conventional modeling techniques demands rigor, precision and certainty, which carry computational cost. On the other hand, soft computing utilizes computation, reasoning and inference to reduce computational cost by exploiting tolerance for imprecision, uncertainty, partial truth and approximation. In addition to computational cost savings, soft computing is an excellent platform for autonomic computing, owing to its roots in artificial intelligence. Wireless communication networks are associated with much uncertainty and imprecision due to a number of stochastic processes such as escalating number of access points, constantly changing propagation channels, sudden variations in network load and random mobility of users. This reality has fuelled numerous applications of soft computing techniques in mobile and wireless communications. This paper reviews various applications of the core soft computing methodologies in mobile and wireless communications

Optimal channel allocation with dynamic power control in cellular networks

Techniques for channel allocation in cellular networks have been an area of intense research interest for many years. An efficient channel allocation scheme can significantly reduce call-blocking and calldropping probabilities. Another important issue is to effectively manage the power requirements for communication. An efficient power control strategy leads to reduced power consumption and improved signal quality. In this paper, we present a novel integer linear program (ILP) formulation that jointly optimizes channel allocation and power control for incoming calls, based on the carrier-to-interference ratio (CIR). In our approach we use a hybrid channel assignment scheme, where an incoming call is admitted only if a suitable channel is found such that the CIR of all ongoing calls on that channel, as well as that of the new call, will be above a specified value. Our formulation also guarantees that the overall power requirement for the selected channel will be minimized as much as possible and that no ongoing calls will be dropped as a result of admitting the new call. We have run simulations on a benchmark 49 cell environment with 70 channels to investigate the effect of different parameters such as the desired CIR. The results indicate that our approach leads to significant improvements over existing techniques.Comment: 11 page

Game-theoretic Resource Allocation Methods for Device-to-Device (D2D) Communication

Device-to-device (D2D) communication underlaying cellular networks allows mobile devices such as smartphones and tablets to use the licensed spectrum allocated to cellular services for direct peer-to-peer transmission. D2D communication can use either one-hop transmission (i.e., in D2D direct communication) or multi-hop cluster-based transmission (i.e., in D2D local area networks). The D2D devices can compete or cooperate with each other to reuse the radio resources in D2D networks. Therefore, resource allocation and access for D2D communication can be treated as games. The theories behind these games provide a variety of mathematical tools to effectively model and analyze the individual or group behaviors of D2D users. In addition, game models can provide distributed solutions to the resource allocation problems for D2D communication. The aim of this article is to demonstrate the applications of game-theoretic models to study the radio resource allocation issues in D2D communication. The article also outlines several key open research directions.Comment: Accepted. IEEE Wireless Comms Mag. 201

An improved multi-agent simulation methodology for modelling and evaluating wireless communication systems resource allocation algorithms

Multi-Agent Systems (MAS) constitute a well known approach in modelling dynamical real world systems. Recently, this technology has been applied to Wireless Communication Systems (WCS), where efficient resource allocation is a primary goal, for modelling the physical entities involved, like Base Stations (BS), service providers and network operators. This paper presents a novel approach in applying MAS methodology to WCS resource allocation by modelling more abstract entities involved in WCS operation, and especially the concurrent network procedures (services). Due to the concurrent nature of a WCS, MAS technology presents a suitable modelling solution. Services such as new call admission, handoff, user movement and call termination are independent to one another and may occur at the same time for many different users in the network. Thus, the required network procedures for supporting the above services act autonomously, interact with the network environment (gather information such as interference conditions), take decisions (e.g. call establishment), etc, and can be modelled as agents. Based on this novel simulation approach, the agent cooperation in terms of negotiation and agreement becomes a critical issue. To this end, two negotiation strategies are presented and evaluated in this research effort and among them the distributed negotiation and communication scheme between network agents is presented to be highly efficient in terms of network performance. The multi-agent concept adapted to the concurrent nature of large scale WCS is, also, discussed in this paper