PHY LAYER SPECIFICATIONS IN THE STANDARD

Operations in high frequencies ranging between 10 and 66 GHz were initially specified in the earlier versions of the 802.16 standard for fixed access. With this specification, only line-of-sight (LOS) signal propagation, with unobstructed path from the transmitter to the receiver, is feasible. Though high-frequency operations have the advantage of less interference, however most wireless technologies prefer lower frequencies because RF signals penetrate structures much better at low frequencies, enabling non-LOS propagation techniques. In non-LOS or multipath propagation modes, the transmitted signals are scattered, reflected, and diffracted by objects in the propagation paths between the transmitter and the receiver as shown in Figure 1. Thus, the receiver receives multiple copies of the transmitted signal, each arriving with different amplitude and phase or delay. These multipath signals may combine destructively at the receiver resulting in severe signal fades. To accommodate services in non-LOS conditions in the WiMAX system, 802.16-2004 standard subsequently specifies operations at lower frequencies, between 2 and 11GHz. Single-carrier transmission, known as wirelessMAN-SC, as well as two multicarrier transmissions, wirelessMAN-OFDM (orthogonal frequency division multiplexing) and wirelessMAN-OFDMA (orthogonal frequency division multiple access) are also specified. The WiMAX system also specified a number of advanced PHY layer and antenna technologies, both fixed and adaptive, to combat the severe fading effect of the multipath propagation channel, to enhance system performance.

 
Figure 1: Non-LOS propagation and intersymbol interference (ISI).

WiMAX PHYSICAL AND MAC LAYERS

WiMAX PHY is responsible for the transmission of data over the air interface (physical medium). The PHY receives MAC layer data packets through its interface with the lowest MAC sublayer, and transmits them according to the MAC layer QoS scheduling. WiMAX MAC layer comprises of three sublayers, which interact through service access points (SAP) to provide the MAC layer services, as shown in Figure 1. The convergence sublayer (CS) interfaces the WiMAX network with other networks by mapping external network data (from ATM, Ethernet, IP, etc.) to the WiMAX system. MAC common part sublayer (MAC CPS) provides majority of the MAC layer services. The MAC CPS receives data from the CS as MAC service data unit (MAC SDU) and efficiently packs them on to the payload of the MAC packet data unit (MAC PDU) through the process of fragmentation and aggregations. Fragmented parts of MAC SDU are used to fill (aggregate) remnant portions of MAC PDU payloads that cannot accommodate full MAC SDU during package. As WiMAX provides connection-oriented service, MAC CPS is also responsible for bandwidth request/reservation for a requested connection, connection establishment, and maintenance. In the WiMAX standard, bandwidth request/reservation is an adaptive process that takes place on a frame-by-frame basis. This allows more efficient resource utilization and optimized performance. Thus the MAC CPS is required to provide up-to-date data on bandwidth request/reservation for each connection, on a frame-by-frame basis. The MAC CPS also provides connection ID for each established connection and marks all MAC PDUs traversing the MAC interface to the PHY with the respective connection ID. This sublayer also performs QoS scheduling by deciding the orders of packet transmissions on the PHY, based on the service flow decided during connection establishments. Privacy sublayer provides authentication to prevent theft of services, and encryption to provide security of services.

 
Figure 1: WiMAX Protocol stack.

The ensemble of the activities of the three sublayers of the WiMAX MAC layer constitutes the MAC layer services. MAC layer services can broadly be categorized into two: periodic and aperiodic activities. Periodic activities are fast- or delay-sensitive types of activities and are carried out to support ongoing communications, thus they must be completed in one frame duration. Examples include QoS scheduling, packing, and fragmentation. Aperiodic activities are slow- or delay-insensitive types of activities. They are executed when and as required by the system, and are not bounded by frame durations. Examples include ranging and authentications for network entry.

OPTIMIZATION IN WIRELESS NETWORK DESIGN

A standard model, suitable for planning purposes, identifies a wireless network with a set of transmitting and receiving antennas scattered over a territory. Such antennas are characterized by a position (geographical coordinates and elevation) and by a number of radio-electrical parameters. The network design process consists in establishing locations and suitable radio-electrical parameters of the antennas. The resulting network is evaluated by means of two basic performance indicators: (1) network coverage, that is the quality of the wanted signals perceived in the target region and (2) network capacity, that is the ability of the network to meet traffic demand. On the basis of quality requirements and projected demand patterns, suitable target thresholds are established for both indicators. In principle, coverage and capacity targets should be pursued simultaneously, as they both depend on the network configuration. However, to handle large real-life instances, conventional network planning resorts to a natural decomposition approach, which consists in performing coverage and capacity planning at different stages. In particular, the network is designed by first placing and configuring the antennas to ensure the coverage of a target area, and then by assigning a suitable number of frequencies to meet (projected) capacity requirements. The final outcome can be simulated and evaluated by an expert, and the whole process can be repeated until a satisfactory result is obtained (Figure 1). Future change in demand patterns can be met by increasing sectorization (i.e., mounting additional antennas in a same site), by selecting new sites, and by assigning additional transmission frequencies).

 
Figure 1: Phases of the conventional planning approach.

The network planning process requires an adequate representation of the territory. In the past years, the standard approach was to subdivide the territory into equally sized hexagons and basic propagation laws were implemented to calculate field strengths. By straightforward analytical computations, these simplified models could provide the (theoretical) position of the antennas and their transmission frequencies. Unfortunately, the approximations introduced by this approach were in most cases unacceptable for practical planning, as the model does not take into account several fundamental factors (e.g., orography of target territories, equipment configurations, actual availability of frequencies and of geographical sites to accommodate antennas, etc.). Furthermore, the extraordinary increase of wireless communication quickly resulted in extremely large networks and congested frequency spectrum, and asked for a better exploitation of the available band. It was soon apparent that effective automatic design algorithms were necessary to handle large instances of complex planning problems, and to improve the exploitation of the scarce radio resources. These algorithms were provided by mathematical optimization. Indeed, already in the early 1980s, it was recognized that the frequency assignment performed at the second stage of the planning process is equivalent to the Graph Coloring Problem (or to its generalizations). The graph coloring problem consists in assigning a color (= frequency) to each vertex (= antenna) of a graph so that adjacent vertices receive different colors and the number of colors is minimum. The graph G = (V, E) associated with the frequency assignments of a wireless network is called interference graph, since edge uv  E represents interference between nodes u  V and v  V and implies that u and v cannot be assigned the same frequency. The graph coloring problem is one of the most known and well studied topics in combinatorial optimization. A remarkable number of exact and heuristic algorithms have been proposed over the years to obtain optimal or suboptimal colorings. Some of these methods were immediately at hand to solve the frequency assignment problem.

The development of mathematical optimization methods triggered the introduction of more accurate representations of the target territories. In particular, also inspired by standard Quality-of-Service (QoS) evaluation methodologies, the coarse hexagonal cells were replaced with (the union of) more handy geometrical entities, namely the demand nodes introduced by Tutschku, and with the now universally adopted testpoints (TP). In the TP model, a grid of approximately squared cells is overlapped to the target area. Antennas are supposed to be located in the center of testpoints: all information about customers and QoS in a TP, such as traffic demand and received signals quality, are aggregated into single coefficients. The TP model allows for smarter representations of the territory, of the actual antennas position, of the signal strengths, and of the demand distributions. This in turn permits a better evaluation of the QoS and, most important, makes it possible to construct more realistic interference graphs, thus leading to improved frequency assignments. Indeed, by means of effective coloring algorithms, it was possible to improve the design of large real-life mobile networks  and also of analogue and digital broadcasting networks.

Finally, basing on the TP model, it was also possible to develop accurate models and effective optimization algorithms to accomplish the first stage of the planning process, namely the coverage phase, to establish suitable positions and radio-electrical parameters for the antennas of a wireless network.

In recent years, thanks to the development of more effective optimization techniques and to the increase of computational power, a number of models integrating coverage and capacity planning have been developed and applied to the design of global system for mobile (GSM) , universal mobile telecommunication system (UMTS), Analog and Digital Video Broadcasting  networks.