In CDMA cellular systems, the frequency reuse factor equals one. Therefore, the soft-handoff technology with combining macroscopic diversity was introduced to enhance the link performance. In this work, a novel macroscopic diversity combining scheme is proposed to enhance the link performance of the forward-link. The basic concept of this scheme is to integrate error correction coding into the soft-handoff technology. According to the number of soft-handoff channels, the source information is encoded by a convolutional code with a lower code rate. The coded symbols are then equally distributed to all channels from different BSs to the MS, and each channel carries a disjointed set of coded symbols. For this proposed scheme, no extra transmission power or bandwidth is required. The only cost is a slight increase of the encoding and decoding complexity of the convolutional codes. Numerical and simulation results show that a performance gain of 1 dB in bit energy-to-total noise power density ratio can be obtained as compared with the conventional scheme in the same conditions.

Traditional soft-handoff algorithms are based on the static threshold handoff algorithm recommended in the IS-95 standard. They are characterized by two parameters, an add threshold Tadd and a drop threshold Tdrop. These two parameters are assumed to have some constant values irrespective of the received signal strength of the pilot in the active set. To improve the performance of the soft-handoff, a dynamic threshold concept was proposed in previous work, where Tadd and Tdrop are dynamically determined according to the received signal strength of the pilot channel in the active set. In this study, previous work of the dynamic threshold algorithm is extended by including additional handoff criteria based on absolute signal strength and/or drop timer. Some functional forms with two new parameters, called boundary thresholds, and slope constant are proposed to dynamically determine Tadd and Tdrop. The dynamic threshold algorithms are compared with static ones in four different cases. Computer simulations show that the dynamic threshold algorithms outperform the static algorithms. We can see that the performance improvements differ from case to case. For example, when a pure dynamic threshold algorithm is compared with a pure static one (case 1), the decrease in the number of active set is about 13.7%. When the absolute threshold and the drop timer are also included in the handoff decision criteria (case 4), however, the decrease is only about 6.2%.

To implement soft handoff in cellular communication systems that employ code division multiple access (CDMA), it is necessary to establish communication lines between the switch and multiple base stations and distribute the communication data via these multi-connections to the base stations simultaneously. This means that, when soft handoff is performed with the same amount of communication line resources as hard handoff, the blocking probability is higher than for hard handoff, and service quality is thus worse. Furthermore, handoffs occur more frequently as the size of cells becomes smaller, and this increases the probability of forced terminations. Switches must be endowed with greater processing capacity to accommodate the more frequent handoffs. The use of the queuing handoff method can be expected, in general, to mitigate forced termination probability compared with the immediate handoff method. In this regard, we propose a prioritized queuing handoff method that gives priority to fast-moving mobile stations (MSs) as a way to mitigate forced terminations even more than the non-priority queuing method without appreciably increasing the processing load. We then compare the traffic characteristics of our proposed method with these of three other methods in micro cell systems--immediate method, non-priority queuing method, and conventional hard handoff method without multi-connections--by computer simulation. Here, considering that the proposed method gives priority to fast-moving calls, traffic characteristics for these methods were evaluated separately for slow- and fast-moving MSs. The results reveal that proposed method can reduce the forced termination probability and total call failure probability more than non-priority queuing method without having an appreciable impact on slow-moving calls.